1001ai — Applied Optimization Engineer
Category: Optimization | Priority: P0 | Headcount: 1
About the role
A hacker-scientist who turns messy customer problems into mathematical optimization models. Mathematically strong and an actual engineer — not a pure researcher.
1001ai is an early-stage startup (~12 people, mostly engineers) building "Scale AI meets Palantir"-style capabilities for heavy-infrastructure clients across aviation, sports, construction, and defense. The core engineering team is largely ex–Scale AI. Roles are based across London and the GCC (Qatar, UAE), with Qatar as the priority location; exceptional candidates can flex on location but should be open to international travel.
Responsibilities
- Translate ambiguous customer problems into tractable optimization formulations.
- Decide when to solve a problem with classical optimization vs. an LLM vs. a more complicated workflow — and ship the answer.
- Scale the RL-guided optimization work.
- Spend focused, dedicated time on the optimizer rather than being spread across product surfaces.
- Calibrate and validate optimization 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, or equivalent), plus Python.
- Very strong mathematically.
- Solid coder with real engineering experience — has shipped, not just prototyped.
- Not super researchy — ships, iterates, and pushes through ambiguity.
- Hacker mindset — strong intuition for where to try, what will work, and when to throw an approach away.
- Bonus: RL or learning-augmented optimization; logistics, scheduling, utilization, or planning experience.
What we value across all engineering hires
- Comfortable in a high-ownership early-stage environment where scope is broad and changes quickly.
- Ships production systems; prior enterprise deployment experience is a major plus.
- Strong engineering judgement over knowledge of one exact tool or framework.
- Pragmatic tradeoffs between speed, quality, security, and maintainability.
- Uses AI coding agents effectively to accelerate implementation but remains fully accountable for code quality, architecture, security, and maintainability.
- Comfortable with hybrid / on-prem / sovereign cloud enterprise deployments.
- A high-performance, "work hard" culture — intense but not toxic.