Senior Machine Learning Engineer, Fulfillment
Instacart · United States - Remote
About this role
**Senior Machine Learning Engineer, Fulfillment — Instacart (Flex First / Remote)** **About Instacart** Instacart is transforming the grocery industry by building intelligent products and platforms that help customers, shoppers, retailers, and brands. Instacart is a **Flex First** team—choose where you do your best work (home, office, or a favorite coffee shop) while staying connected through regular in-person events. **Overview** The Enterprise AI organization builds intelligent products and platforms using **machine learning, optimization, and software engineering**. In this role, you’ll design, build, and deploy **production machine learning systems** that create measurable business impact—owning the full lifecycle from problem formulation and data development through experimentation, deployment, monitoring, and continuous improvement. **What you’ll do** - Design, implement, and deploy ML models and services for high-impact Enterprise AI products and business initiatives. - Own the full ML lifecycle: problem formulation, data preparation, feature development, model training, offline evaluation, experimentation, production rollout, and ongoing monitoring. - Build reliable, scalable, maintainable software in **Python** with strong engineering practices (testing, profiling, code review, documentation, operational readiness). - Partner with product, engineering, data science, and business stakeholders to define success metrics, prioritize work, and deliver measurable outcomes. - Develop and operate ML services on cloud infrastructure with monitoring, alerting, observability, and production safeguards. - Use experimentation, statistical analysis, and causal/counterfactual evaluation to assess model quality and guide launch decisions. - Shape technical direction through design reviews, architecture discussions, and thoughtful evaluation of modeling approaches and infrastructure tradeoffs. - Contribute to engineering culture through knowledge sharing, mentoring, improving development practices, and operational support for critical services. **About you** You bring strong ML and software engineering fundamentals, communicate clearly across disciplines, and take ownership from idea through production—motivated by measurable impact and practical, scalable solutions. **Minimum qualifications** - Bachelor’s degree (CS/Engineering/Math/Stats or related) or equivalent practical experience. - 5+ years of professional experience developing and deploying ML models/systems in production. - Proficiency in **Python** and **SQL**, including production-quality code with automated testing, profiling, debugging, and code review. - Experience across the complete ML lifecycle (data prep, feature engineering, evaluation, experimentation, deployment, monitoring). - Experience building/operating ML services or data products in a cloud environment (GCP or AWS). - Experience with containerized services and production software practices (e.g., **Docker**, CI, monitoring/alerting, incident response). - Demonstrated ability to work cross-functionally to define requirements and deliver measurable outcomes. **Preferred qualifications** - Master’s or PhD in a quantitative field. - Experience designing ML systems for large-scale, high-throughput, or low-latency applications. - Familiarity with distributed data processing, streaming systems, feature stores, or real-time feature computation. - Experience with model serving/orchestration and ML platforms (e.g., Kubern
Listing freshness
CronJobs last confirmed this listing 1h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.