Senior Machine Learning Engineer II, Fulfillment, Matching and Positioning

Instacart

Posted 3mo ago

The employer’s full description could not be read from their board. This is a summary of the posting — follow the apply link for the original.

Build production-grade optimization and ML solutions
Design, implement, and deploy algorithms for order batching, shopper routing, and marketplace positioning
Own the full model lifecycle
Build reliable, low-latency services
Partner with product, operations, and data science to define roadmaps and success metrics
Leverage experimentation and causal methods to validate changes
Contribute to engineering excellence through code reviews and design docs
Mentor peers and raise the technical bar

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 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

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

Skills