@ 1001ai
Applied Optimization Engineer — 1001 (1001.ai). P0. $30M Series A AI company building an RL-guided optimizer for enterprise/industrial problems. London/Europe, hybrid, GCC travel.
Hacker-scientist who turns messy customer problems into mathematical optimization models. Mathematically strong AND an actual engineer — not a pure researcher. Translates ambiguous customer problems into tractable optimization formulations; decides when to solve with classical optimization vs an LLM vs a more complex workflow — and ships the answer; scales RL-guided optimization work; calibrates and validates models against real production data.
REQUIREMENTS: 3-5 years applying optimization to real industrial problems IN PRODUCTION (not academia only). Hands-on with at least one industrial-strength solver stack (Gurobi, CPLEX, OR-Tools, Pyomo, JuMP, Hexaly, or equivalent) plus Python. Very strong mathematically (top-school math/CS/OR background or competition math signal). Solid coder with real engineering experience — has shipped, not just prototyped. Not super researchy — ships, iterates, pushes through ambiguity. Hacker mindset: strong intuition for what to try and when to abandon an approach. Bonus: RL or learning-augmented optimization; logistics, scheduling, utilization, or planning domains.
CALIBRATION (ruthless — client: "Our engineers are from top labs and top schools. I expect at least the same bar"): target operations-research/optimization engineers at companies with famous OR practice (Amazon SCOT/fulfillment, Google OR-tools team, DeepMind, Uber/Lyft marketplace, Deliveroo/Ocado/Flexport logistics, airlines OR, Palantir, Gurobi/Hexaly themselves, quant funds), or top-school OR/math PhDs-turned-engineers who ship. London/Europe strongly preferred. NOT pure academics with no production code, NOT data scientists who only did A/B tests, NOT supply-chain analysts using Excel/Tableau.