Senior Machine Learning Engineer, Matching & Positioning
Company: Instacart
Location: Remote
About Instacart
Instacart is transforming the grocery industry by connecting people with the food they love and more time to enjoy it together. We believe in serving the varied needs of our community by delivering an essential service that customers rely on. We offer flexible earnings opportunities to Instacart Personal Shoppers and are building a team to push our mission forward.
Instacart operates on a Flex First model, empowering employees to choose where they do their best work while fostering connection through regular in-person events.
About the Role
Join Instacart's Logistics organization as a Senior Machine Learning Engineer on the Matching & Positioning team. This tight-knit group of 9 engineers and scientists focuses on real-time decisioning for order batching, shopper routing, and assignment within our dynamic, multi-sided marketplace. You will work at the intersection of operations research, combinatorial optimization, and machine learning to design and ship algorithms that directly impact profitability, on-time delivery, shopper experience, and customer satisfaction at scale. You'll collaborate closely with engineering, product, and data science partners to translate ambiguous problems into well-formed optimization and ML systems operating under sub-second latency and high throughput. If you thrive in a fast-paced environment and want to see your models make real-world decisions every minute of every day, this team is for you.
Responsibilities
- Design, implement, and deploy production-grade optimization and ML solutions for order batching, real-time shopper assignment, routing, and marketplace positioning using techniques like MIP/CP-SAT, heuristics/metaheuristics, and learning-to-rank.
- Own the full model lifecycle: problem formulation, data pipelines and features, offline evaluation and simulation, A/B testing, staged rollouts, and ongoing monitoring/observability.
- Build reliable, low-latency services in Python (and potentially C++ or Go for performance-critical components) that integrate with solvers (e.g., OR-Tools, Gurobi, CPLEX) and run on cloud infrastructure with Docker/Kubernetes.
- Partner with product, operations, and data science to define roadmaps and success metrics, delivering measurable impact to on-time rates, shopper utilization, cost per order, and customer experience.
- Leverage experimentation and causal methods, along with offline counterfactual replay/simulation, to validate changes and de-risk launches.
- Contribute to engineering excellence through code reviews, design docs, robust testing, and participation in an on-call rotation for mission-critical fulfillment services; mentor peers and raise the technical bar.
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 like 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.
- 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.
- Experience participating in an on-call rotation for production ML/optimization services.
Compensation & Benefits
Instacart provides highly market-competitive compensation and benefits. This role is remote.
Base Pay Ranges (USD):
- CA, NY, CT, NJ: $240,000—$253,500
- WA: $230,000—$243,000
- OR, DE, ME, MA, MD, NH, RI, VT, DC, PA, VA, CO, TX, IL, HI: $221,000—$233,000
- All other states: $201,000—$212,000
Offers may vary based on experience and skills. This role is also eligible for new hire and annual equity grants.