About The Position

We are hiring a Staff or Senior Applied Scientist to build and deploy advanced AI/GenAI and ML systems grounded in applied mathematics and Operations Research (OR). This role is ideal for someone who can take ambiguous, high-impact operational problems, turn them into clear mathematical/algorithmic formulations, and lead implementation end-to-end—including writing production-quality code. You’ll work at the intersection of optimization, inference science, NLP, and reinforcement learning, with a strong emphasis on practical delivery and measurable business outcomes. Supply chain optimization experience is a plus.

Requirements

  • Strong applied mathematics background with depth in Operational Research, including one or more of: Linear / Mixed-Integer Optimization (LP/MIP)
  • Constraint Programming
  • Network / Graph Optimization
  • Stochastic / Robust Optimization
  • Simulation, heuristics, or metaheuristics
  • Research or applied experience in at least one of: Inference science (e.g., causal inference, Bayesian methods, uncertainty modeling)
  • NLP (e.g., retrieval, embeddings, information extraction, LLM systems)
  • Reinforcement Learning (e.g., bandits, sequential decision-making, offline RL)
  • Proven ability to implement algorithms and deliver real systems end-to-end.
  • Strong coding skills in Python and familiarity with relevant scientific/ML tooling.

Nice To Haves

  • Experience in supply chain optimization (planning, inventory, logistics, fulfillment, scheduling).
  • Experience building GenAI/LLM-enabled decision systems (e.g., RAG, tool-augmented agents, evaluation frameworks).
  • Background shipping applied science solutions into production environments.

Responsibilities

  • Problem formulation: Translate business challenges into mathematical and computational models.
  • Applied research: Evaluate and adapt existing approaches (OR models, AI/ML, GenAI/LLM methods).
  • Algorithm development: Design and implement new algorithms when existing solutions fall short.
  • Hands-on execution: Build prototypes, run experiments, and lead production implementation (you code).
  • Technical leadership: Drive solution architecture, performance evaluation, and operational readiness.
  • Collaboration: Partner with product, engineering, and domain teams to deliver scalable solutions.

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What This Job Offers

Job Type

Full-time

Career Level

Mid Level

Education Level

Ph.D. or professional degree

Number of Employees

501-1,000 employees

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