Senior Machine Learning Engineer II, Fulfillment, Matching and Positioning

Minimum Qualifications

• Bachelor’s degree in Computer Science, Operations Research, Electrical Engineering, Applied Mathematics, or a related field (or equivalent practical experience).
• 5+ years of professional experience building and shipping ML and/or optimization systems to production.
• 3+ years formulating and solving large-scale combinatorial optimization problems (e.g., VRP, matching, scheduling) using solvers such as OR-Tools, Gurobi, or CPLEX (MIP/CP-SAT) and heuristic methods.
• Proficiency in Python and SQL, including writing production-quality code with testing, profiling, and code review practices.
• Hands-on experience deploying algorithms/models as microservices with Docker and Kubernetes on a major cloud provider (GCP or AWS), including monitoring, alerting, and dashboards.
• Experience designing and operating low-latency decision services in high-throughput environments (targeting sub-second P95 response times).
• Practical experience with A/B testing or online experimentation platforms, from hypothesis through analysis and rollout decisions.
• Strong collaboration and communication skills with engineering, product, and data science stakeholders.

Preferred Qualifications

• Master’s or PhD in Operations Research, Computer Science, Electrical Engineering, Applied Mathematics, or a related quantitative field.
• Domain experience in logistics, ride-hailing, delivery, or marketplace optimization at scale.
• Familiarity with reinforcement learning or contextual bandits for online decision-making and exploration/exploitation tradeoffs.
• Experience with geospatial data, routing APIs, and graph algorithms.
• Background in building simulation frameworks and counterfactual evaluation for decision systems.
• Experience with streaming data and real-time feature computation (e.g., Kafka, Flink) and feature stores.
• Proficiency in C++ or Go for performance-critical components.
• Track record of mentoring engineers and leading cross-functional projects to measurable outcomes.
• Experience participating in an on-call rotation for production ML/optimization services.

#LI-Remote

Instacart provides highly market-competitive compensation and benefits in each location where our employees work. This role is remote and the base pay range for a successful candidate is dependent on their permanent work location. Please review our Flex First remote work policy here.

Offers may vary based on many factors, such as candidate experience and skills required for the role. Additionally, this role is eligible for a new hire equity grant as well as annual refresh grants. Please read more about our benefits offerings here.…