Python Developer Jobs - Beirut Lebanon

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Automation &amp; Digitalization / AI &amp; Solution Development:</p><p><br></p><p>Computer Science / Strong analytical and problem-solving skills with a foundation in software development (Python/JavaScript) and a keen interest in AI, automation, and digital systems.</p><p><br></p><p>Candidates should be self-motivated, fast learners with the ability to adapt quickly, work collaboratively, and translate ideas into practical, scalable solutions.</p><p><br></p><p>Work schedule is part time preferably on-premises, Monday to Friday from 10am to 3pm, with flexible hybrid option available. Candidate monthly fee will range from 150$ to 300$ per month based on candidate skills and previous expertise (if any).</p><p><br></p><p>We require candidates to be living in or very near to Beirut. We do not accept candidates who live far from Beirut.</p></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><p>Computer Science / Strong analytical and problem-solving skills with a foundation in software development (Python/JavaScript) and a keen interest in AI, automation, and digital systems.</p><p>Candidates should be self-motivated, fast learners with the ability to adapt quickly, work collaboratively, and translate ideas into practical, scalable solutions.</p><p>Work schedule is part time preferably on-premises, Monday to Friday from 10am to 3pm, with flexible hybrid option available.</p><p>We require candidates to be living in or very near to Beirut. We do not accept candidates who live far from Beirut.</p><p></p></section>

Automation & Digitalization / AI & Solution Development: <br> <br>Computer Science / Strong analytical and problem-solving skills with a foundation in software development (Python/JavaScript) and a keen interest in AI, automation, and digital systems. <br> <br>Candidates should be self-motivated, fast learners with the ability to adapt quickly, work collaboratively, and translate ideas into practical, scalable solutions. <br> <br>Work schedule is part time preferably on-premises, Monday to Friday from 10am to 3pm, with flexible hybrid option available. Candidate monthly fee will range from 150$ to 300$ per month based on candidate skills and previous expertise (if any). <br> <br>We require candidates to be living in or very near to Beirut. We do not accept candidates who live far from Beirut. <br> <br>Interested candidates, please send your CV & intro letter via email. <br> <br>Best wishes, <br>Mohamad-Rabih Chatila <br>CEO

GlobeMed Group, the largest Healthcare Benefits Management company in the MENA region is looking for a Senior AI / ML Engineer who will be responsible for designing, developing, integrating, and deploying AI capabilities across GlobeMed. The role provides senior technical expertise in AI engineering, application development, while working closely with business and technical teams to deliver reliable, scalable, and secure AI capabilities aligned with organizational needs. <br> <br>Duties & Responsibilities: <br> <br> Design and develop AI capabilities, applications, and AI-enabled workflows using modern AI tools and frameworks. <br> Develop and integrate AI agents, APIs, and MCP-based capabilities where applicable. <br> Develop and maintain front-end and back-end components supporting AI applications. <br> Apply AI-assisted coding tools to improve development efficiency and code quality. <br> Evaluate and adopt emerging AI technologies, frameworks, and development practices. <br> Ensure AI solutions are designed with appropriate scalability, reliability, security, and maintainability. <br> Work with ICT teams to ensure appropriate infrastructure, networking, security, and resource requirements are addressed. <br> Monitor and optimize the technical performance and resource utilization of AI environments. <br> Lead technical testing and validation of AI solutions prior to implementation. <br> Evaluate AI solutions for accuracy, reliability, performance, usability, and scalability. <br> Identify technical and functional issues and coordinate their resolution. <br> Establish appropriate testing approaches for AI models, agents, integrations, and applications. <br> Training, evaluating, and fine-tuning ML models on historical data for predictive analysis. <br> <br>Qualifications <br> <br>Education: <br> <br> Bachelor's degree in Computer Science, Software Engineering, Artificial Intelligence, Information Technology, or a related technical field. <br> Relevant Master's degree or professional AI/cloud certification is an advantage. <br> <br>Experience/Knowledge: <br> <br> 3-6 years of experience in AI Platforms. <br> Strong hands-on experience developing and deploying AI applications and capabilities. <br> Strong knowledge of modern AI tools, frameworks, APIs, LLMs, and AI development practices. <br> Experience with AI agents, MCPs, and AI integrations. <br> Experience using AI coding and AI-assisted software development tools. <br> Experience working with legacy Databases using SQL. <br> Hands on code knowledge using python or other similar languages. <br> Source Control platform integration example GIT. <br> Previous experience working with microservices <br> Prior work experience with message queues and streaming platforms is a plus. <br> Knowledge of Agile methodology with prior experience on ticketing systems like jira is a plus. <br> Experience working on ML models with hands on experience using platforms like pytorch. <br> Hands on model testing, metrics evaluation, and fine tuning for ML predictive models

Company Description - Software Solutions is a leading provider of software and IT solutions with over 35 years of experience, serving clients in Lebanon, Saudi Arabia, Qatar, and across the MENA region. Supported by a team of more than 200 professionals, the company delivers high-quality, integrated solutions that streamline business processes and enable digital transformation. The company offers a wide range of products, including ERP systems with HR and payroll modules, specialized payroll and school systems, POS, e-commerce platforms, mobile sales automation, and warehouse management solutions. The company maintains strong partnerships with global technology leaders such as SAP, Microsoft, LS Retail, Odoo, and others, ensuring access to advanced tools and best practices. With a robust project management approach, the company focuses on seamless implementation and tailored solutions that help organizations grow and operate more efficiently. <br> <br>Role Description The Senior Odoo Support Specialist is a full-time, on-site role based in Ras Beirut. This role is responsible for providing high-level technical and functional support to clients experiencing issues with their Odoo ERP systems across all modules. Day-to-day tasks include receiving escalated customer calls, analyzing and diagnosing complex system problems across accounting, sales, inventory, HR, payroll, manufacturing, CRM, project management, e-commerce, and other Odoo modules, guiding users through troubleshooting steps, and ensuring timely resolution of Odoo-related inquiries. The specialist collaborates closely with clients and internal technical teams to resolve software bugs, configure system workarounds, optimize Odoo modules, and support system updates or enhancements. The role also involves documenting support cases, conducting root-cause analysis, providing training on module-specific features, and contributing to the continuous improvement of the company's Odoo support services and knowledge base. <br> <br>Qualifications <br> <br> <br> <br> Candidates should possess strong skills in Odoo ERP Administration and Support across multiple modules, including configuration, troubleshooting, and system maintenance. <br> Candidates should possess comprehensive knowledge of core Odoo modules including Accounting, Sales, Inventory, HR, Payroll, Manufacturing, CRM, Project Management, E-Commerce, and Warehouse Management. <br> Candidates should possess solid Customer Service and Technical Support knowledge, with experience in handling escalated calls and managing client expectations in a multi-module environment. <br> Candidates should possess robust Analytical Skills, including the ability to interpret error logs, diagnose software issues across different modules, and propose effective technical solutions. <br> Candidates should possess understanding of complex Business Processes and workflows across various departments and their integration within the Odoo ecosystem. <br> Bachelor's degree in Computer Science, Information Systems, Business Administration, or a related technical field. <br> Experience implementing or providing advanced support for Odoo ERP across multiple modules or similar comprehensive business software solutions. <br> Familiarity with ITIL practices and ticketing systems for managing customer support requests. <br> Strong communication and client-facing skills, with the ability to explain complex technical concepts to non-technical users over the phone and conduct training sessions. <br> Proficiency in Python and PostgreSQL is an advantage for understanding Odoo's backend structure and customizing solutions. <br> Ability to work collaboratively in cross-functional teams and manage multiple urgent client issues effectively

<section><p class="heading jdMain">Job Description</p><p class="heading">Roles &amp; Responsibilities</p><div class="paragraph"><p>Join our team to design, build, and maintain reliable software systems that enable scalable product delivery and continuous improvement. You ll work closely with cross-functional partners to ship features on schedule, enhance performance and reliability, and strengthen code quality while supporting deployments and service monitoring.</p><p>Create and maintain robust, production-ready software solutions by applying strong programming skills, API and database expertise, and disciplined engineering practices (testing, version control, and CI/CD) to reduce defects, improve reliability, and deliver measurable performance and maintainability gains.</p><p>Job Duties and Responsibilities</p><ul><li>Programming (Java/Python/JavaScript/C#)</li><li>API Development (REST/GraphQL)</li><li>Database Design (SQL/NoSQL)</li><li>Version Control (Git)</li><li>Testing (unit/integration)</li><li>Cloud &amp; CI/CD Concepts</li><li>Problem-solving</li><li>Collaboration and teamwork</li><li>Clear communication</li><li>Ownership and accountability</li><li>Performance &amp; Reliability Optimization</li><li>Production Incident Management</li><li>Deployment Support &amp; Service Monitoring</li><li>Code Quality &amp; Maintainability</li><li>Defect Fixing</li></ul></div></section><section><p class="heading">Desired Candidate Profile</p><p class="paragraph"></p><ul><li>Programming (Java/Python/JavaScript/C#)</li><li>APIs (REST/GraphQL)</li><li>Databases (SQL/NoSQL)</li><li>Version control (Git)</li><li>Testing (unit/integration)</li><li>Cloud/CI/CD concepts</li><li>Problem-solving</li><li>Collaboration and teamwork</li><li>Clear communication</li><li>Ownership and accountability</li></ul><p></p></section>

We are looking for a data-driven Growth Marketing Specialist to manage and optimize digital marketing performance across regional markets. <br> <br>Key Responsibilities: <br> <br>* Manage Google Ads & Meta Ads campaigns <br>* Monitor and optimize CAC & ROAS <br>* Analyze performance using GA4 & Looker Studio <br>* Support A/B testing, lead generation & funnel optimization <br>* Manage GTM, tracking & marketing data integrations <br>* Coordinate with agencies, media partners & branches <br>* Support website, Google Business Profile & seasonal campaigns <br>* Monitor market trends and competitors <br> <br>Requirements: <br> <br>* 2–4 years of experience in performance/digital marketing <br>* Hands-on experience with Google Ads, Meta Ads & GA4 <br>* Strong Google Sheets & Looker Studio skills <br>* Basic SQL, Python or Google Apps Script is a plus <br>* Highly analytical, detail-oriented and organized

We are looking for a Lead BI Engineer to lead a data team and drive the company’s data, reporting, and BI strategy. <br> <br>Key Responsibilities: <br>• Lead and mentor a team of data engineers, developers & BI analysts <br>• Own data prioritization, roadmap & stakeholder management <br>• Oversee data architecture, pipelines and BI infrastructure <br>• Drive reliable dashboards, KPIs and management reporting <br>• Ensure data quality, documentation and engineering standards <br>• Translate business needs into effective technical solutions <br> <br>Requirements: <br>• 6+ years in Data Engineering, Analytics Engineering or BI Engineering <br>• 2+ years leading/managing engineers <br>• Strong Python, SQL & data modeling skills <br>• Experience with dbt or similar transformation frameworks <br>• Experience owning a data platform from ingestion to reporting <br>• Strong communication and stakeholder management skills <br>• Willingness to travel based on business needs

<p>We are looking for a skilled Full Stack Developer to join our technology team and contribute to the design, development, and enhancement of scalable, secure, and high-performance web applications.</p><p>The ideal candidate will have strong hands-on experience with Python, Django, Django REST Framework (DRF), PostgreSQL, Redis, JavaScript, and jQuery, with the ability to work across both backend and frontend development.</p><p><strong>Desired Candidate Profile</strong></p><ul><li>3 5+ years of professional experience in full stack web development.</li><li>Strong proficiency in Python.</li><li>Solid hands-on experience with Django.</li><li>Strong experience developing APIs using Django REST Framework (DRF).</li><li>Strong knowledge of PostgreSQL, including database design, SQL queries, indexing, and optimization.</li><li>Practical experience with Redis for caching, session management, queues, or performance optimization.</li><li>Strong knowledge of JavaScript and jQuery.</li><li>Good understanding of HTML5 and CSS3.</li><li>Experience integrating frontend applications with RESTful APIs.</li><li>Strong understanding of object-oriented programming, MVC/MVT architecture, and software design principles.</li><li>Good understanding of web application security, authentication, authorization, and API security.</li><li>Experience with Git and version control systems.</li><li>Strong troubleshooting, debugging, and analytical skills.</li><li>Ability to write clean, structured, scalable, and maintainable code.</li><li>Good understanding of software development lifecycle and Agile methodologies.</li></ul>

<p>About the job: This is the horizontal role of the three Leads, and a standalone one same Lead level as the Support Operations Lead and Customer Success Lead, but leading a function, not a team. Where the Support Operations Lead owns support and the Customer Success Lead owns the customer journey, this Lead makes both run with less manual effort mapping their processes and automating them while owning installations and provisioning directly. What's already in place: an AI Tier 1 support layer that fronts all support, and early onboarding automation (e.g., the go-live billing hand-off). This role scales and deepens that across Operations. Flagship focus areas Customer Onboarding automate deal closed setup go-live: ticket creation, cross-system data sync, task orchestration, status tracking, and comms. (Partner: Customer Success Lead.) Installations &amp; Provisioning turn manual setup and configuration into scripted, repeatable, and where possible self-service processes. Enhance the AI Support Layer our support already runs through an AI Tier 1 layer. Extend and improve it: better resolution and deflection, smarter routing, and readiness for the new web PMS (new content, new workflows, new edge cases). (Partner: Support Operations Lead.)</p><p>What you'll do</p><ul><li>Set the automation &amp; AI roadmap for Operations prioritizing opportunities with the Director and the two other Leads by impact.</li><li>Map processes end-to-end and find where automation or AI fits.</li><li>Build the automations yourself API integrations across HubSpot, Zendesk, and internal tools; scripts (PowerShell / Python); scheduled jobs; and native workflows (HubSpot, Zendesk, Power Automate).</li><li>Automate installations scripted, templated, repeatable provisioning.</li><li>Advance the existing AI Tier 1 layer improve resolution/deflection, tune routing, and extend its coverage as the new web PMS rolls out.</li><li>Apply AI more broadly ticket triage/classification, data cleanup, drafting, and agent-style task automation using LLM tools (e.g., Claude).</li><li>Own data &amp; reporting make the impact visible: time saved, faster cycle times, fewer errors.</li><li>Work safely dry-runs, staging, idempotency, documentation, and clean handoff to IT for production.</li><li>Set the standard reusable patterns and lightweight governance so automations are reliable and maintainable, not one-off hacks</li></ul><p>Self-directed builder owns the roadmap and standards and executes them personally; comfortable being the sole driver of the function. Comfortable with REST APIs (auth, JSON, pagination, rate limits). Scripting in PowerShell and/or Python. Hands-on with a CRM or ticketing platform (HubSpot and/or Zendesk) and its automation tools. Experience building or tuning AI/LLM workflows (e.g., support automation, classification, agents). Process mapping sees where automation fits in a manual workflow. Solid data handling (CSV/Excel, matching/merging; SQL a plus). A test-first, careful mindset. Nice to have iPaaS / data-sync tools (HubSpot Data Sync, Zapier, Make). Scripted provisioning / deployment experience. Git, and a background in SaaS, hospitality tech, or support operations. Success looks like Onboarding and installations that largely run themselves. The AI support layer resolving more, routing better, and ready for the new web PMS. Reliable integrations that don't need babysitting. A measurable drop in manual work across Operations visible to leadership.</p><p><strong>Desired Candidate Profile</strong></p><p>Self-directed builder owns the roadmap and standards and executes them personally; comfortable being the sole driver of the function. Comfortable with REST APIs (auth, JSON, pagination, rate limits). Scripting in PowerShell and/or Python. Hands-on with a CRM or ticketing platform (HubSpot and/or Zendesk) and its automation tools. Experience building or tuning AI/LLM workflows (e.g., support automation, classification, agents). Process mapping sees where automation fits in a manual workflow. Solid data handling (CSV/Excel, matching/merging; SQL a plus). A test-first, careful mindset. Nice to have iPaaS / data-sync tools (HubSpot Data Sync, Zapier, Make). Scripted provisioning / deployment experience. Git, and a background in SaaS, hospitality tech, or support operations.</p>

<p>Aspire Software is looking for a Data Scientist to join our team in Lebanon. Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio. About the job: We are looking for a Senior Machine Learning Engineer who wants to own that evolution. This is not a research-only role. You will frame problems, explore data, design models, build evaluation systems, investigate real customer issues, and ship production services. Your work will influence real pricing decisions and measurable hotel revenue not just dashboards or internal prototypes. What You'll Work On -Pricing intelligence: Advance our pricing engine using probabilistic forecasting, elasticity estimation, contextual bandits, reinforcement learning, and other appropriate optimization methods. Demand forecasting: Improve booking-curve and final-occupancy forecasts, including uncertainty estimates that can inform safer pricing decisions. Safe experimentation: Build historical replay, simulation, backtesting, shadow deployment, and controlled rollout capabilities to measure revenue impact before models affect customers. Production ML: Turn models into reliable, tested, and observable Python services, owning the path from experimentation through deployment, monitoring, and rollback. Problem-solving and customer investigations: Debug unexpected pricing, data, integration, and production behavior. Trace customer-reported issues to their root cause and turn incidents into lasting improvements. Data and intelligent experiences: Strengthen the reservation, occupancy, competitor-rate, PMS, and event-data pipelines behind our decisions, while contributing to AI-powered explanations and revenue-manager tools. Tech Stack Python 3.11, FastAPI, Pydantic, SQLAlchemy 2.0, and Alembic PostgreSQL/Supabase and Redis Pandas, Polars, NumPy, and statsmodels OpenAI, Anthropic, LangChain, and LangGraph PredictHQ and multiple hotel PMS and market-data integrations AWS ECS/Fargate, SQS, EventBridge, S3, and CloudWatch Docker, GitHub Actions, Prometheus, and PostHog</p><p><strong>Desired Candidate Profile</strong></p><ul><li>Experience taking machine-learning systems from problem definition through production deployment and monitoring.</li><li>Strong Python and SQL skills, including experience building modular, typed, tested production software not only exploratory notebooks.</li><li>A solid foundation in statistics, experimentation, forecasting, and model evaluation.</li><li>Experience working with time-dependent, noisy, incomplete, or imperfect real-world data.</li><li>Strong analytical problem-solving skills and a methodical approach to ambiguous technical issues.</li><li>Proven ability to debug production systems, including data pipelines, APIs, asynchronous jobs, integrations, and model behavior.</li><li>Experience investigating customer-reported issues, identifying root causes, and communicating findings clearly to technical and non-technical stakeholders.</li><li>A habit of improving systems after incidents through better tests, monitoring, documentation, safeguards, or architecture.</li><li>The judgment to balance model sophistication with reliability, explainability, and business value.</li><li>Comfort working with APIs, relational databases, containers, cloud infrastructure, and CI/CD.</li><li>Clear communication skills and an ability to work closely with engineers, product leaders, revenue-management experts, and customer-facing teams.</li><li>A high level of ownership: you can turn an ambiguous business or customer problem into a practical, measurable plan and carry it through to completion.</li><li>Years of experience are a useful signal, but not the deciding factor. We care more about what you have built, how you reason, and how you respond when models and systems meet the real world.</li><li>Nice to Have You do not need everything on this list: Contextual bandits, reinforcement learning, recommendation systems, bidding, or other sequential decision systems.</li><li>Probabilistic demand forecasting or hierarchical Bayesian modeling.</li><li>Pricing, revenue management, marketplaces, travel, hospitality, advertising, or e-commerce.</li><li>Causal inference and off-policy evaluation.</li><li>Model drift, data-quality monitoring, and experiment-tracking systems.</li><li>Multi-tenant SaaS or event-driven architectures.</li><li>Debugging distributed systems and third-party integrations in production.</li><li>LLM applications and agentic workflows.</li><li>AWS services such as ECS, SQS, EventBridge, S3, and CloudWatch.</li><li>Hospitality experience is welcome, but not required. We will help you learn the domain.</li></ul>

<h2 class="h5">Job description</h2> <div class="t-break" data-jb-field="description"> <span>Aspire Software is looking for a Data Scientist to join our team in Lebanon.<br> Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals.<br> By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.<br> About the job: We are looking for a Senior Machine Learning Engineer who wants to own that evolution.<br> This is not a research-only role.<br> You will frame problems, explore data, design models, build evaluation systems, investigate real customer issues, and ship production services.<br> Your work will influence real pricing decisions and measurable hotel revenue not just dashboards or internal prototypes.<br> What You'll Work On -Pricing intelligence: Advance our pricing engine using probabilistic forecasting, elasticity estimation, contextual bandits, reinforcement learning, and other appropriate optimization methods.<br> Demand forecasting: Improve booking-curve and final-occupancy forecasts, including uncertainty estimates that can inform safer pricing decisions.<br> Safe experimentation: Build historical replay, simulation, backtesting, shadow deployment, and controlled rollout capabilities to measure revenue impact before models affect customers.<br> Production ML: Turn models into reliable, tested, and observable Python services, owning the path from experimentation through deployment, monitoring, and rollback.<br> Problem-solving and customer investigations: Debug unexpected pricing, data, integration, and production behavior.<br> Trace customer-reported issues to their root cause and turn incidents into lasting improvements.<br> Data and intelligent experiences: Strengthen the reservation, occupancy, competitor-rate, PMS, and event-data pipelines behind our decisions, while contributing to AI-powered explanations and revenue-manager tools.<br> Tech Stack Python 3.<br>11, FastAPI, Pydantic, SQLAlchemy 2.<br>0, and Alembic PostgreSQL/Supabase and Redis Pandas, Polars, NumPy, and statsmodels OpenAI, Anthropic, LangChain, and LangGraph PredictHQ and multiple hotel PMS and market-data integrations AWS ECS/Fargate, SQS, EventBridge, S3, and CloudWatch Docker, GitHub Actions, Prometheus, and PostHog Experience taking machine-learning systems from problem definition through production deployment and monitoring.<br> Strong Python and SQL skills, including experience building modular, typed, tested production software—not only exploratory notebooks.<br> A solid foundation in statistics, experimentation, forecasting, and model evaluation.<br> Experience working with time-dependent, noisy, incomplete, or imperfect real-world data.<br> Strong analytical problem-solving skills and a methodical approach to ambiguous technical issues.<br> Proven ability to debug production systems, including data pipelines, APIs, asynchronous jobs, integrations, and model behavior.<br> Experience investigating customer-reported issues, identifying root causes, and communicating findings clearly to technical and non-technical stakeholders.<br> A habit of improving systems after incidents through better tests, monitoring, documentation, safeguards, or architecture.<br> The judgment to balance model sophistication with reliability, explainability, and business value.<br> Comfort working with APIs, relational databases, containers, cloud infrastructure, and CI/CD.<br> Clear communication skills and an ability to work closely with engineers, product leaders, revenue-management experts, and customer-facing teams.<br> A high level of ownership: you can turn an ambiguous business or customer problem into a practical, measurable plan and carry it through to completion.<br> Years of experience are a useful signal, but not the deciding factor.<br> We care more about what you have built, how you reason, and how you respond when models and systems meet the real world.<br> Nice to Have You do not need everything on this list: Contextual bandits, reinforcement learning, recommendation systems, bidding, or other sequential decision systems.<br> Probabilistic demand forecasting or hierarchical Bayesian modeling.<br> Pricing, revenue management, marketplaces, travel, hospitality, advertising, or e-commerce.<br> Causal inference and off-policy evaluation.<br> Model drift, data-quality monitoring, and experiment-tracking systems.<br> Multi-tenant SaaS or event-driven architectures.<br> Debugging distributed systems and third-party integrations in production.<br> LLM applications and agentic workflows.<br> AWS services such as ECS, SQS, EventBridge, S3, and CloudWatch.<br> Hospitality experience is welcome, but not required.<br> We will help you learn the domain.<br> What We Value Speed with quality — Ship fast, but ship code and models a staff engineer would approve AI-native workflow — You don't just know about AI tools, you use them daily to write, debug, and architect Ownership — Pick up a problem and drive it to completion without hand-holding Simplicity — Elegant solutions over over-engineered ones.<br> Minimal code that does the job Curiosity — Our domain (hotel revenue optimization) has real depth.<br> You're excited to learn it</span> </div>

<p><h4>About the company</h4> <p>Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.</p> <h4>About the job</h4> <p>We are looking for a senior machine learning engineer who wants to own that evolution. This is not a research-only role. You will frame problems, explore data, design models, build evaluation systems, investigate real customer issues, and ship production services. Your work will influence real pricing decisions and measurable hotel revenue not just dashboards or internal prototypes.</p> <h4>What you'll work on</h4> <ul> <li><strong>Pricing intelligence:</strong> Advance our pricing engine using probabilistic forecasting, elasticity estimation, contextual bandits, reinforcement learning, and other appropriate optimization methods.</li> <li><strong>Demand forecasting:</strong> Improve booking-curve and final-occupancy forecasts, including uncertainty estimates that can inform safer pricing decisions.</li> <li><strong>Safe experimentation:</strong> Build historical replay, simulation, backtesting, shadow deployment, and controlled rollout capabilities to measure revenue impact before models affect customers.</li> <li><strong>Production ML:</strong> Turn models into reliable, tested, and observable Python services, owning the path from experimentation through deployment, monitoring, and rollback.</li> <li><strong>Problem-solving and customer investigations:</strong> Debug unexpected pricing, data, integration, and production behavior. Trace customer-reported issues to their root cause and turn incidents into lasting improvements.</li> <li><strong>Data and intelligent experiences:</strong> Strengthen the reservation, occupancy, competitor-rate, PMS, and event-data pipelines behind our decisions, while contributing to AI-powered explanations and revenue-manager tools.</li> </ul> <h4>Tech stack</h4> <ul> <li>Python 3.11, FastAPI, Pydantic, SQLAlchemy 2.0, and Alembic</li> <li>PostgreSQL/Supabase and Redis</li> <li>Pandas, Polars, NumPy, and statsmodels</li> <li>OpenAI, Anthropic, LangChain, and LangGraph</li> <li>PredictHQ and multiple hotel PMS and market-data integrations</li> <li>AWS ECS/Fargate, SQS, EventBridge, S3, and CloudWatch</li> <li>Docker, GitHub Actions, Prometheus, and PostHog</li> </ul> <h4>Requirements</h4> <ul> <li>Experience taking machine-learning systems from problem definition through production deployment and monitoring.</li> <li>Strong Python and SQL skills, including experience building modular, typed, tested production software—not only exploratory notebooks.</li> <li>A solid foundation in statistics, experimentation, forecasting, and model evaluation.</li> <li>Experience working with time-dependent, noisy, incomplete, or imperfect real-world data.</li> <li>Strong analytical problem-solving skills and a methodical approach to ambiguous technical issues.</li> <li>Proven ability to debug production systems, including data pipelines, APIs, asynchronous jobs, integrations, and model behavior.</li> <li>Experience investigating customer-reported issues, identifying root causes, and communicating findings clearly to technical and non-technical stakeholders.</li> <li>A habit of improving systems after incidents through better tests, monitoring, documentation, safeguards, or architecture.</li> <li>The judgment to balance model sophistication with reliability, explainability, and business value.</li> <li>Comfort working with APIs, relational databases, containers, cloud infrastructure, and CI/CD.</li> <li>Clear communication skills and an ability to work closely with engineers, product leaders, revenue-management experts, and customer-facing teams.</li> <li>A high level of ownership: you can turn an ambiguous business or customer problem into a practical, measurable plan and carry it through to completion.</li> <li>Years of experience are a useful signal, but not the deciding factor. We care more about what you have built, how you reason, and how you respond when models and systems meet the real world.</li> </ul> <h4>Nice to have</h4> <p>You do not need everything on this list:</p> <ul> <li>Contextual bandits, reinforcement learning, recommendation systems, bidding, or other sequential decision systems.</li> <li>Probabilistic demand forecasting or hierarchical Bayesian modeling.</li> <li>Pricing, revenue management, marketplaces, travel, hospitality, advertising, or e-commerce.</li> <li>Causal inference and off-policy evaluation.</li> <li>Model drift, data-quality monitoring, and experiment-tracking systems.</li> <li>Multi-tenant SaaS or event-driven architectures.</li> <li>Debugging distributed systems and third-party integrations in production.</li> <li>LLM applications and agentic workflows.</li> <li>AWS services such as ECS, SQS, EventBridge, S3, and CloudWatch.</li> <li>Hospitality experience is welcome, but not required. We will help you learn the domain.</li> </ul> <h4>What we value</h4> <ul> <li>Speed with quality — ship fast, but ship code and models a staff engineer would approve.</li> <li>AI-native workflow — you don't just know about AI tools, you use them daily to write, debug, and architect.</li> <li>Ownership — pick up a problem and drive it to completion without hand-holding.</li> <li>Simplicity — elegant solutions over over-engineered ones. Minimal code that does the job.</li> <li>Curiosity — our domain (hotel revenue optimization) has real depth. You're excited to learn it.</li> </ul></p><p></p>

<p>Aspire Software is looking for a Data Scientist to join our team in Lebanon. Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.</p><p>About the job: We are looking for a Senior Machine Learning Engineer who wants to own that evolution. This is not a research-only role. You will frame problems, explore data, design models, build evaluation systems, investigate real customer issues, and ship production services. Your work will influence real pricing decisions and measurable hotel revenue not just dashboards or internal prototypes.</p><p>What You'll Work On</p><ul><li>Pricing intelligence: Advance our pricing engine using probabilistic forecasting, elasticity estimation, contextual bandits, reinforcement learning, and other appropriate optimization methods.</li><li>Demand forecasting: Improve booking-curve and final-occupancy forecasts, including uncertainty estimates that can inform safer pricing decisions.</li><li>Safe experimentation: Build historical replay, simulation, backtesting, shadow deployment, and controlled rollout capabilities to measure revenue impact before models affect customers.</li><li>Production ML: Turn models into reliable, tested, and observable Python services, owning the path from experimentation through deployment, monitoring, and rollback.</li><li>Problem-solving and customer investigations: Debug unexpected pricing, data, integration, and production behavior. Trace customer-reported issues to their root cause and turn incidents into lasting improvements.</li><li>Data and intelligent experiences: Strengthen the reservation, occupancy, competitor-rate, PMS, and event-data pipelines behind our decisions, while contributing to AI-powered explanations and revenue-manager tools.</li></ul><p>Tech Stack</p><ul><li>Python 3.11, FastAPI, Pydantic, SQLAlchemy 2.0, and Alembic</li><li>PostgreSQL/Supabase and Redis</li><li>Pandas, Polars, NumPy, and statsmodels</li><li>OpenAI, Anthropic, LangChain, and LangGraph</li><li>PredictHQ and multiple hotel PMS and market-data integrations</li><li>AWS ECS/Fargate, SQS, EventBridge, S3, and CloudWatch</li><li>Docker, GitHub Actions, Prometheus, and PostHog</li></ul><p><strong>Desired Candidate Profile</strong></p><ul><li>Experience taking machine-learning systems from problem definition through production deployment and monitoring.</li><li>Strong Python and SQL skills, including experience building modular, typed, tested production software not only exploratory notebooks.</li><li>A solid foundation in statistics, experimentation, forecasting, and model evaluation.</li><li>Experience working with time-dependent, noisy, incomplete, or imperfect real-world data.</li><li>Strong analytical problem-solving skills and a methodical approach to ambiguous technical issues.</li><li>Proven ability to debug production systems, including data pipelines, APIs, asynchronous jobs, integrations, and model behavior.</li><li>Experience investigating customer-reported issues, identifying root causes, and communicating findings clearly to technical and non-technical stakeholders.</li><li>A habit of improving systems after incidents through better tests, monitoring, documentation, safeguards, or architecture.</li><li>The judgment to balance model sophistication with reliability, explainability, and business value.</li><li>Comfort working with APIs, relational databases, containers, cloud infrastructure, and CI/CD.</li><li>Clear communication skills and an ability to work closely with engineers, product leaders, revenue-management experts, and customer-facing teams.</li><li>A high level of ownership: you can turn an ambiguous business or customer problem into a practical, measurable plan and carry it through to completion.</li><li>Years of experience are a useful signal, but not the deciding factor. We care more about what you have built, how you reason, and how you respond when models and systems meet the real world.</li></ul><p>Nice to Have</p><ul><li>You do not need everything on this list:</li><li>Contextual bandits, reinforcement learning, recommendation systems, bidding, or other sequential decision systems.</li><li>Probabilistic demand forecasting or hierarchical Bayesian modeling.</li><li>Pricing, revenue management, marketplaces, travel, hospitality, advertising, or e-commerce.</li><li>Causal inference and off-policy evaluation.</li><li>Model drift, data-quality monitoring, and experiment-tracking systems.</li><li>Multi-tenant SaaS or event-driven architectures.</li><li>Debugging distributed systems and third-party integrations in production.</li><li>LLM applications and agentic workflows.</li><li>AWS services such as ECS, SQS, EventBridge, S3, and CloudWatch.</li><li>Hospitality experience is welcome, but not required. We will help you learn the domain.</li></ul><p>What We Value</p><ul><li>Speed with quality: Ship fast, but ship code and models a staff engineer would approve</li><li>AI-native workflow: You don't just know about AI tools, you use them daily to write, debug, and architect</li><li>Ownership: Pick up a problem and drive it to completion without hand-holding</li><li>Simplicity: Elegant solutions over over-engineered ones. Minimal code that does the job</li><li>Curiosity: Our domain (hotel revenue optimization) has real depth. You're excited to learn it</li></ul>

Job Summary: <br>We are looking for a highly skilled AI Engineer with 2 to 5 years of experience to design, develop, and deploy cutting-edge AI and machine learning solutions. <br>In this role, you will work with large datasets, build intelligent models, and drive innovation by leveraging advanced AI techniques. <br>You will collaborate with cross-functional teams to integrate AI capabilities into business applications, ensuring scalability, efficiency, and real-world impact. <br>If you have a strong foundation in machine learning, deep learning, and AI-driven problem-solving, and you're eager to push the boundaries of technology, we want to hear from you. <br>Job Responsibilities: <br>• Develop, train, and deploy machine learning models to solve business challenges. <br>• Work with large datasets to extract insights, clean, and preprocess data. <br>• Optimize model performance, accuracy, and efficiency. <br>• Design and implement AI algorithms for task, computer vision, or predictive analytics. <br>• Collaborate with data scientists, software engineers, and business stakeholders to integrate AI solutions. <br>• Stay up to date with the latest advancements in AI/ML and apply innovative techniques. <br>• Ensure scalability and efficiency of AI solutions in production environments. <br>• Troubleshoot and fine-tune models for performance improvement. <br>Required Qualifications & Skills: <br>• Education: Bachelor’s degree in computer science, AI, Data Science, Data Analytics or a related field. <br>• Experience: 2-5 years of hands-on experience in AI/ML development, power BI, copilot studio, generative AI, and AI agent <br>• Proficiency in Python, experience with large datasets, data preprocessing, and feature engineering. <br>• AI Specialization: Strong understanding of deep learning <br>• Problem-Solving: Ability to analyse complex problems and implement AI-driven solutions. <br>• Strong communication skills to work effectively with cross-functional teams

Company Description <br>RAY Labs is a PropTech company based in Beirut, focused on addressing the pain points related to space and community management. Our core product is a mobile and web SaaS platform offering dynamic features, allowing property, facility, and community managers to efficiently manage communities and spaces. By equipping stakeholders with the relevant capabilities and tools, our platform improves operational efficiency, payment convenience, community engagement, and reduces administrative work. <br> <br>Position Overview <br>As a Junior DevOps Engineer, you will play a key role in modernizing the development and deployment lifecycles of our company, by collaborating with our development teams to build and maintain development/deployment pipelines. <br> <br>Responsibilities <br>· Automate deployment, scaling, and management of containerized applications using Kubernetes (on Azure services and on VMs) <br>· Maintain and enhance CI/CD pipelines in Jenkins for our codelines: <br>· Backend (PHP, Java) <br>· Frontend (Angular) <br>· Mobile (iOS, Android) <br>· Deploy and manage monitoring and logging tools to provide centralized reporting for production environments, as well as alerts when critical issues occur. <br>· Assist developers in monitoring, troubleshooting, and resolving issues in production environments. <br> <br>Requirements <br>· 1+ years of experience in a DevOps or related role. <br>· Basic understanding of Kubernetes (min. 6 months hands-on experience or certification). <br>· Experience with CI/CD tools (Jenkins, GitLab CI, Azure DevOps, or equivalent). <br>· Familiarity with cloud platforms, particularly Azure (knowledge of AWS or GCP is a plus). <br>· Experience with containerization technologies (Docker). <br>· Knowledge of infrastructure as code tools (Terraform, Ansible, Helm, or similar). <br>· Experience with version control (Git). <br>· Basic scripting knowledge (Bash, Python, Groovy, or similar). <br>· Excellent problem-solving skills and attention to detail. <br>· Strong communication and teamwork abilities

<p><h4>Aspire Software company overview</h4> <p>Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.</p> <h4>About the job</h4> <p>This is a builder role for someone obsessed with what agents can actually do in production. You'll design and ship autonomous AI systems that operate inside the Polygon marketplace — agents that understand jewelry listings, assist buyers and sellers, surface intelligence across decades of trade data, and automate workflows that have been manual for forty years. You won't just be wiring up LLM calls. You'll be designing agentic systems end-to-end: tool definitions, planning loops, memory, evals, guardrails, observability, and the product surfaces that put these capabilities in front of real users.</p> <h4>Key responsibilities</h4> <li>Design and build agentic systems that power core marketplace experiences — listing intelligence, semantic and multi-step search, buyer/seller assistants, trade matching, content moderation, and market analytics</li> <li>Architect tool-using agents with reliable planning, execution, and recovery</li> <li>Build the supporting infrastructure: RAG pipelines, vector search, evals, prompt management, traceability, and cost/latency monitoring</li> <li>Partner with product and design to translate agentic capabilities into UX that members actually use and trust</li> <li>Establish patterns and primitives so the rest of the engineering team can ship agent-powered features confidently</li> <li>Stay on the frontier — evaluate new models, frameworks, and techniques and bring the ones that matter into production</li> <h4>Requirements</h4> <li>3 - 5 years of experience</li> <li>Production experience building agentic systems with LLMs — not just chat wrappers, but agents that plan, use tools, and complete multi-step tasks</li> <li>Deep familiarity with at least one major LLM API (Anthropic, OpenAI, or equivalent), including tool use / function calling, structured outputs, and streaming</li> <li>Experience designing and running evals for non-deterministic systems</li> <li>Strong software engineering fundamentals — TypeScript/Python, modern web stack, API design</li> <li>Pragmatic judgment about when to use agents, when to use simpler pipelines, and when not to use AI at all</li></p><p></p>

<p><h4>Description</h4> <p>Aspire Software is looking for an AI engineer to join our team in Lebanon.</p> <p>Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.</p> <h4>About the job</h4> <p>This is a builder role for someone obsessed with what agents can actually do in production. You'll design and ship autonomous AI systems that operate inside the Polygon marketplace — agents that understand jewelry listings, assist buyers and sellers, surface intelligence across decades of trade data, and automate workflows that have been manual for forty years. You won't just be wiring up LLM calls. You'll be designing agentic systems end-to-end: tool definitions, planning loops, memory, evals, guardrails, observability, and the product surfaces that put these capabilities in front of real users.</p> <h4>Key responsibilities</h4> <li>Design and build agentic systems that power core marketplace experiences — listing intelligence, semantic and multi-step search, buyer/seller assistants, trade matching, content moderation, and market analytics</li> <li>Architect tool-using agents with reliable planning, execution, and recovery</li> <li>Build the supporting infrastructure: RAG pipelines, vector search, evals, prompt management, traceability, and cost/latency monitoring</li> <li>Partner with product and design to translate agentic capabilities into UX that members actually use and trust</li> <li>Establish patterns and primitives so the rest of the engineering team can ship agent-powered features confidently</li> <li>Stay on the frontier — evaluate new models, frameworks, and techniques and bring the ones that matter into production</li> <h4>Requirements</h4> <li>3 - 5 years of experience</li> <li>Production experience building agentic systems with LLMs — not just chat wrappers, but agents that plan, use tools, and complete multi-step tasks</li> <li>Deep familiarity with at least one major LLM API (Anthropic, OpenAI, or equivalent), including tool use / function calling, structured outputs, and streaming</li> <li>Experience designing and running evals for non-deterministic systems</li> <li>Strong software engineering fundamentals — TypeScript/Python, modern web stack, API design</li> <li>Pragmatic judgment about when to use agents, when to use simpler pipelines, and when not to use AI at all</li></p><p></p>

<p><h4>Aspire Software company overview</h4> <p>Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.</p> <h4>About the job</h4> <p>This is a builder role for someone obsessed with what agents can actually do in production. You'll design and ship autonomous AI systems that operate inside the Polygon marketplace — agents that understand jewelry listings, assist buyers and sellers, surface intelligence across decades of trade data, and automate workflows that have been manual for forty years. You won't just be wiring up LLM calls. You'll be designing agentic systems end-to-end: tool definitions, planning loops, memory, evals, guardrails, observability, and the product surfaces that put these capabilities in front of real users.</p> <h4>Key responsibilities</h4> <li>Design and build agentic systems that power core marketplace experiences — listing intelligence, semantic and multi-step search, buyer/seller assistants, trade matching, content moderation, and market analytics</li> <li>Architect tool-using agents with reliable planning, execution, and recovery</li> <li>Build the supporting infrastructure: RAG pipelines, vector search, evals, prompt management, traceability, and cost/latency monitoring</li> <li>Partner with product and design to translate agentic capabilities into UX that members actually use and trust</li> <li>Establish patterns and primitives so the rest of the engineering team can ship agent-powered features confidently</li> <li>Stay on the frontier — evaluate new models, frameworks, and techniques and bring the ones that matter into production</li> <h4>Requirements</h4> <li>3 - 5 years of experience</li> <li>Production experience building agentic systems with LLMs — not just chat wrappers, but agents that plan, use tools, and complete multi-step tasks</li> <li>Deep familiarity with at least one major LLM API (Anthropic, OpenAI, or equivalent), including tool use / function calling, structured outputs, and streaming</li> <li>Experience designing and running evals for non-deterministic systems</li> <li>Strong software engineering fundamentals — TypeScript/Python, modern web stack, API design</li> <li>Pragmatic judgment about when to use agents, when to use simpler pipelines, and when not to use AI at all</li></p><p></p>

<p><h4>Description</h4> <p>Aspire Software is looking for an AI engineer to join our team in Lebanon.</p> <p>Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.</p> <h4>About the job</h4> <p>This is a builder role for someone obsessed with what agents can actually do in production. You'll design and ship autonomous AI systems that operate inside the Polygon marketplace — agents that understand jewelry listings, assist buyers and sellers, surface intelligence across decades of trade data, and automate workflows that have been manual for forty years. You won't just be wiring up LLM calls. You'll be designing agentic systems end-to-end: tool definitions, planning loops, memory, evals, guardrails, observability, and the product surfaces that put these capabilities in front of real users.</p> <h4>Key responsibilities</h4> <li>Design and build agentic systems that power core marketplace experiences — listing intelligence, semantic and multi-step search, buyer/seller assistants, trade matching, content moderation, and market analytics</li> <li>Architect tool-using agents with reliable planning, execution, and recovery</li> <li>Build the supporting infrastructure: RAG pipelines, vector search, evals, prompt management, traceability, and cost/latency monitoring</li> <li>Partner with product and design to translate agentic capabilities into UX that members actually use and trust</li> <li>Establish patterns and primitives so the rest of the engineering team can ship agent-powered features confidently</li> <li>Stay on the frontier — evaluate new models, frameworks, and techniques and bring the ones that matter into production</li> <h4>Requirements</h4> <li>3 - 5 years of experience</li> <li>Production experience building agentic systems with LLMs — not just chat wrappers, but agents that plan, use tools, and complete multi-step tasks</li> <li>Deep familiarity with at least one major LLM API (Anthropic, OpenAI, or equivalent), including tool use / function calling, structured outputs, and streaming</li> <li>Experience designing and running evals for non-deterministic systems</li> <li>Strong software engineering fundamentals — TypeScript/Python, modern web stack, API design</li> <li>Pragmatic judgment about when to use agents, when to use simpler pipelines, and when not to use AI at all</li></p><p></p>

<p>You will build AI features end to end: the model or pipeline that produces the decision, the service that runs it, and the product surface where a revenue manager sees and acts on it. This is not a research role and it is not a pure app-dev role it is the bridge between them. Examples of what you'd own in your first year:</p><ul><li>Forecasting and rate-recommendation logic that feeds our auto-publish engine, including the guardrails that keep recommendations inside a property's tolerance</li><li>LLM-driven features: natural-language explanations of why a rate moved, conversational querying of a property's performance, automated market commentary</li><li>Rate-intelligence pipelines ingesting competitor rates, cleaning messy third-party data, and turning it into signals the model can trust</li><li>Evaluation harnesses and monitoring so we know when a model degrades before a customer does</li><li>The full-stack surface around all of the above: APIs, data models, and the UI that exposes them</li></ul><p>3 5 years building and shipping production software, with meaningful AI/ML work in that time</p><p>Strong Python; comfortable in TypeScript/JavaScript for the application layer</p><p>Hands-on experience with LLM APIs (Anthropic, OpenAI or similar) prompt design, structured output, tool use, retrieval, and the evaluation discipline to know whether any of it is working</p><p>Solid SQL and data modeling; you can reason about a schema and write queries that don't melt the database</p><p>Experience with at least one of: time-series forecasting, pricing/optimization models, or recommendation systems</p><p>Comfort with messy, incomplete, real-world data third-party feeds, inconsistent APIs, partial history</p><p>Cloud deployment experience and familiarity with modern CI/CD</p><p>Nice To Have:</p><ul><li>Hospitality, travel, pricing, or marketplace domain experience</li><li>Experience integrating with PMS, channel manager, or booking-engine APIs</li><li>Background in a small startup where you owned a system rather than a ticket queue</li></ul><p>How we work, and who succeeds here</p><p>We hire for ownership as much as for stack. The engineers who do well:</p><ul><li>Take technical ownership. You're handed a problem, not a spec. You decide what to build, flag the trade-offs, and are accountable for the result in production including when it breaks at an inconvenient hour.</li><li>Are intrinsically driven. Nobody will watch your calendar. You choose the right next thing to work on when the direction is ambiguous, and you finish things.</li><li>Communicate well asynchronously. Written updates that a busy reader can act on. You surface blockers early rather than going quiet. Clear, complete PR descriptions and issue comments.</li><li>Manage your own time zone. You're responsible for maintaining reliable overlap with the team and for being predictable about when you're reachable.</li></ul><p><strong>Desired Candidate Profile</strong></p><p>3 5 years building and shipping production software, with meaningful AI/ML work in that time</p><p>Strong Python; comfortable in TypeScript/JavaScript for the application layer</p><p>Hands-on experience with LLM APIs (Anthropic, OpenAI or similar) prompt design, structured output, tool use, retrieval, and the evaluation discipline to know whether any of it is working</p><p>Solid SQL and data modeling; you can reason about a schema and write queries that don't melt the database</p><p>Experience with at least one of: time-series forecasting, pricing/optimization models, or recommendation systems</p><p>Comfort with messy, incomplete, real-world data third-party feeds, inconsistent APIs, partial history</p><p>Cloud deployment experience and familiarity with modern CI/CD</p>