Instacart
Grocery
SeniorMachineLearningEngineerII,Fulfillment,MatchingandPositioning
“Senior Machine Learning Engineer II, Fulfillment, Matching and Positioning at Instacart. Skills: Machine learning, Optimization, Software engineering, Logistics. Deliver measurable impact to on-time rates, shopper utilization,. Leverage experimentation and causal methods along with offline”
What You'll Achieve.
Deliver measurable impact to on-time rates; Deliver measurable impact to shopper utilization; Deliver measurable impact to cost per order; Deliver measurable impact to customer experience
Industry & Context.
Combinatorial optimization; Root cause analysis
On-call rotation
What They're Looking For.
Must Have
Bachelor's degree in Computer Science, Operations Research, Electrical Engineering, Applied Mathematics, or related field (or equivalent practical experience), 5+ years 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, Collaboration and communication skills with engineering, product, and data science stakeholders
Nice to Have
Master's or PhD in Operations Research, Computer Science, Electrical Engineering, Applied Mathematics, or 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
What You'll Do.
Deliver measurable impact to on-time rates
Leverage experimentation and causal methods along with offline
Contribute to engineering excellence through code reviews
Mentor peers and raise the technical bar
Pair deep toolkit in operations research and machine
Motivated by real-world impact
Communicate clearly with cross-functional partners
Take ownership from ideation to production
How You'll Work.
Team & Collaboration
Cross-functional partners; Engineering stakeholders; Product stakeholders; Data science stakeholders
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