Operations Research & Optimization Engineer

About OrbitronAIOrbitronAI is on a mission to turn large language model magic into production-grade agentic systems and workflows that solve real problems for the world’s largest enterprises. We’ve recently raised $10 million in seed fundingand are scaling fast across Dubai, Bengaluru, and Saudi Arabia.The Team Behind OrbitronAIFounded by an exceptional leadership team of: Former EY Partners and Ex-CTOs and Heads of Engineering from successful Series B+ startups. The founding team brings together seasoned business, product and engineering leaders who have built and scaled large organizations and have led enterprise projects valued at over $1 billion.Why Join OrbitronAI?- Massive Impact, Real Ownership → Ship end-to-end features, own outcomes, and see your work power mission-critical systems. - Battle-Tested Leadership → Learn and grow with seasoned leaders who bring deep industry expertise and zero ego. - Cutting Edge Stack → Work with GenAI frontier models, Java, Python, Go, TypeScript, GCP & edge compute, Vector DBs, DAG engines.Our Cultural DNA- Hustle → Move with urgency, bias for action, celebrate shipping. - Ownership & Commitment → Act like a founder — your decisions shape the company. - Founder’s Mindset → Challenge ideas, not people. Seek truth, not consensus. - Continuous Learning → No legacy thinking; we invest in upskilling and sponsor courses &Why This RoleAirline crew rostering is one of the most complex real-world optimization challenges, thousands ofconstraints, millions of possibilities, and zero room for error.We’re not looking for someone to maintain spreadsheets or tune simple heuristics. We’re building autonomous decision-making systems that blend classical optimization, AI, and domain intelligence to generate schedules that are safe, efficient, and disruption resilient. You’ll be the technical owner of our optimization engine, modelling constraints, building solvers, runninglarge-scale experiments and ultimately shipping a system that an entire industry depends on.Bonus: we’re a company where using AI tools to accelerate your own workflow is not just allowed; it’s expected.What You Bring1. Bachelor’s or master’s degree in Operations Research, Computer Science, Industrial Engineering, Applied Mathematics, or equivalent practical experience2. 5+ years of experience building or operating large-scale optimization or scheduling systems3. Strong expertise in one or more optimization techniques:a. Mixed-Integer Programming (MIP)b. Constraint Programming (CP)c. Heuristics / Metaheuristics (GA, Tabu, Simulated Annealing, LNS, etc.)d. Column generation or decomposition methods4. Hands-on experience with optimization tools like Gurobi, CPLEX, OR-Tools, MiniZinc, Pyomo,or custom solvers5. Ability to model complex rule systems (legalities, constraints, fatigue rules, preferences, unions,etc.)6. Proficiency in Python (bonus: experience in C++ for performance-critical components)7. Familiarity with ML-assisted optimization is a plus (RL, heuristic learning, forecasting, or delaymodelling)8. Experience designing experiments, tuning solvers, and interpreting model output.9. Strong understanding of production engineering practices: CI/CD, version control, testingframeworks, monitoring.10. Excellent communication and collaboration skills; ability to thrive in a fast-paced, problem-solving, startup environment.What You’ll Do1. Design, build, and optimize the core scheduling engine for airline crew and cabin rosters — fromconstraint modelling to solver implementation.2. Build scalable, parameterized formulations for pairing, rostering, bidding, fatigue compliance,legality checks, and disruption recovery.3. Develop and tune algorithms (MIP, CP, heuristics, or hybrids) capable of handling very largeproblem instances.4. Create automated pipelines to run “what-if” scenarios, simulations, and optimizationexperiments.5. Integrate real-world data sources — schedules, crew profiles, aircraft rotations, rule sets — intothe optimization engine.6. Collaborate closely with product, domain experts, and engineering teams to define rules,constraints, and objective functions.7. Experiment quickly: prototype new formulations, prune search spaces, evaluate heuristics, andbenchmark solver performance.8. Work with AI/ML engineers to blend optimization with predictive modelling, reinforcementlearning, or heuristic learning where beneficial.9. Help define reliability, feasibility guarantees, and quality metrics for solver outputs.10. Turn complex airline rules into simple, elegant models that consistently produce feasible andhigh-quality schedules.11. Contribute to building the next generation of autonomous operational decision systems usedinside enterprise environments.Perks & Benefits- Top‑Tier Compensation & stock options with substantial potential upside. - Latest MacBook Pros + 4K monitors - Paid AI tool & cloud credits to experiment freely - Premium health, wellness, and learning budgets - A culture celebrating every victory. - Continuous learning and skill development opportunities.

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