Senior Machine Learning Engineer (Fulfillment, Matching and Positioning)

Role overview

Join Instacart’s Logistics organization as a Senior Machine Learning Engineer. You’ll build systems for real-time decision-making across order batching, shopper routing, and assignment/marketplace positioning, directly impacting profitability, on-time delivery, and customer satisfaction.

Responsibilities

• Design, implement, and deploy optimization/ML algorithms for:
  • order batching
  • real-time shopper assignment
  • routing
  • marketplace positioning
• Use techniques including MIP/CP-SAT, heuristics/metaheuristics, and learning-to-rank.
• Own the full model lifecycle:
  • problem formulation
  • data pipelines and feature engineering
  • offline evaluation and simulation
  • A/B testing and staged rollouts
  • ongoing monitoring/observability
• Build reliable, low-latency services in Python (and performance-critical parts in C++ or Go) that integrate with solvers (e.g., OR-Tools, Gurobi, CPLEX) and run on Docker/Kubernetes in the cloud.
• Profile and optimize to meet high-throughput, sub-second P95 response time targets.

Requirements

• Strong operations research + ML toolkit and solid software engineering fundamentals.
• Python and SQL proficiency; write production-quality code with testing, profiling, and code reviews.
• Experience building microservices for algorithms/models using Docker and Kubernetes on a major cloud provider (GCP or AWS), including monitoring/alerting/dashboards.
• Experience designing/operating low-latency decision services in high-throughput environments (targeting sub-second P95).
• 3+ years formulating and solving large-scale combinatorial optimization (e.g., VRP, matching, scheduling) with solvers such as OR-Tools, Gurobi, CPLEX (including MIP/CP-SAT) and heuristics.
• 5+ years building and shipping ML and/or optimization systems to production.
• Experience with A/B testing or online experimentation platforms (hypothesis → analysis → rollout).
• Strong cross-functional communication and ownership from ideation to production.

Nice to have

• Master’s or PhD in a quantitative field (OR/CS/EE/Applied Math or related).
• Domain experience in logistics, ride-hailing, delivery, or marketplace optimization.
• Building simulation frameworks and counterfactual evaluation for decision systems.
• Familiarity with reinforcement learning or contextual bandits.
• Experience with geospatial data, routing APIs, and graph algorithms.
• Experience with streaming data and real-time feature computation (Kafka, Flink) and feature stores.
• Performance-critical coding experience in C++ or Go.
• Mentoring engineers, leading cross-functional projects, and measurable outcomes.
• Participation in an on-call rotation for production ML/optimization services.