Senior Machine Learning Engineer II, Fulfillment, Matching and Positioning

🔥 1 minute ago

🏄 California, Colorado, +17 more states – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🦌 Connecticut – Remote 🏛️ District of Columbia – Remote 🌺 Hawaii – Remote 🌽 Illinois – Remote 🦞 Maine – Remote 🗻 New Hampshire – Remote 🏖️ New Jersey – Remote 🗽 New York – Remote 🌲 Oregon – Remote 🦀 Maryland – Remote 🍂 Massachusetts – Remote 🔔 Pennsylvania – Remote ⚓ Rhode Island – Remote 🤠 Texas – Remote 🍁 Vermont – Remote ⚔️ Virginia – Remote ☕ Washington – Remote

💵 $201k - $253.5k / year

⏰ Full Time

🟠 Senior

🤖 Machine Learning Engineer

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Instacart

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2012

🛍️ eCommerce

🚗 Transport

🛒 Retail

💰 $232M Venture Round on 2021-11

eCommerce • Transport • Retail

Instacart is a company that offers a flexible approach to work while transforming the grocery industry. It provides an essential service by delivering groceries and household goods to customers' doors in as little as 30 minutes. Instacart offers safe and flexible earning opportunities to personal shoppers and tackles challenges such as rerouting deliveries during snowstorms and connecting customers with coupons and deals. It aims to be the operating system for the grocery industry, thus helping customers save time for other activities. Instacart emphasizes diversity, equity, and belonging in its work culture.

📋 Description

• Build production-grade optimization and ML solutions that drive Instacart’s fulfillment decisions end-to-end in a rapidly evolving, high-scale environment. • Design, implement, and deploy algorithms for order batching, real-time shopper assignment, routing, and marketplace positioning using techniques such as 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, where performance dictates, C++ or Go) 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; deliver 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.

🎯 Requirements

• 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.

🏖️ Benefits

• Competitive salary • Flex First team approach • New hire equity grant • Annual refresh grants