Senior Optimization / Algorithms Engineer

Job description

We are looking for a Senior/Lead Optimization/Algorithms Engineer to design and build the combinatorial optimization core that powers topology-aware TPU scheduling, translating scheduling constraints into solvable mathematical models.

Responsibilities

- Develop the combinatorial solver core for TPU slice placement

- Build MIP/CP-SAT models representing multi-host slice constraints

- Perform latency profiling to ensure sub-second solve times at scale

- Translate Kubernetes CRD/Pod spec constraints into abstract graph/optimization models

- Collaborate with AI/ML Performance Engineers to incorporate empirical hardware coefficients into the cost model

Requirements

- Strong background in combinatorial optimization, operations research, or algorithms engineering

- Experience with MIP/CP-SAT solvers (e.g., OR-Tools, Gurobi, CPLEX)

- Proficiency in Python and/or Golang

- Understanding of graph theory and constraint satisfaction problems

- Familiarity with performance profiling and latency-critical systems

Nice to have

- Prior exposure to Kubernetes scheduling internals

- Experience with distributed systems optimization