Senior Machine Learning Engineer, Operations Research

About the role

Instacart is actively seeking a Senior Machine Learning Engineer with a robust foundation in Operations Research to integrate into the Service Availability & Routing team, which sits within the broader Logistics organization structure. In this specific capacity, the successful candidate will be responsible for owning the complete end-to-end lifecycle of operations research initiatives, which involves designing, developing, and executing models that directly govern the movement and assignment of orders across the platform ecosystem. The role provides an opportunity to make a direct and measurable impact on both the shopper experience and the overall efficiency of platform-level operations while handling significant scale. You will engage with high-impact challenges that are central to the business, including but not limited to order batching strategies, shopper routing optimization, service availability prediction, and real-time task assignment logic. Instacart maintains a Flex First work policy, which allows for remote work arrangements while still fostering close collaboration with a wide array of cross-functional partners and stakeholders. This position represents a critical role in bridging advanced algorithmic research with practical, large-scale deployment in a dynamic marketplace environment.

Key facts

This position is physically based in the United States but offers remote work eligibility to its incumbents, providing geographical flexibility for the right candidate. The role is classified as full-time, requiring standard commitment and engagement levels associated with senior technical positions. The compensation package for this role is specified within a range of $180,000.00 to $280,000.00 on a per-year basis, reflecting the scope and impact of the responsibilities. You will be embedded within the Logistics & ML group, a specific unit responsible for the intelligence and execution behind Instacart's core fulfillment system and its associated workflows. The primary mission of this group is to optimize a complex multi-sided marketplace, ensuring that customers receive their orders in a timely and high-quality manner, that shoppers receive efficient and fulfilling work assignments, and that retail partners and consumer brands achieve reasonable and viable business outcomes.

What you'll do

You will be tasked with designing intricate intake logic for orders, ensuring that routing models can effectively process and handle variability in demand patterns and strict operational constraints.

You will build and maintain sophisticated optimization pipelines that intelligently combine traditional mathematical programming approaches with modern learning-based machine learning methods.

You will regularly review algorithmic results and model outputs in partnership with product managers and business stakeholders to confirm quality, feasibility, and alignment before any operational rollout or deployment.

You will be responsible for shipping models into production environments, establishing robust monitoring frameworks that track system stability and measure tangible business impact over time.

You will engage in frequent collaboration across various internal teams to align on strategic objectives and to surface new constraints or evolving requirements early in the model development lifecycle.

You will explore and evaluate advanced graph and combinatorial techniques to solve complex problems inherent in batching, matching, and scheduling challenges.

You will translate ambiguous business rules and requirements into precise mathematical formulations that solvers can execute efficiently at Instacart's massive scale and volume.

You will maintain clarity regarding model assumptions and decision logic to ensure that downstream teams can trust the outputs and act confidently on model recommendations.

Requirements

To be considered for this role, you must possess three or more years of industry experience specifically applying machine learning methodologies to large datasets within real-world, production-grade settings.

Your background must include strong, demonstrable programming skills in Python, coupled with fluency in SQL, Pandas, and machine learning tools such as scikit-learn, XGBoost, Keras, or TensorFlow.

You must possess sharp analytical thinking and a proven ability to solve complex problems within complex and dynamic operational environments.

You must be an effective communicator who can collaborate seamlessly with diverse stakeholders, including technical and non-technical personnel across all organizational levels and functions.

You hold a graduate degree in Operations Research, Industrial Engineering, or a closely related technical field that provides a strong foundation in quantitative methods.

Nice to have

The ideal candidate may have prior exposure to deep learning frameworks and advanced methodologies, which could provide an edge in handling specific model architectures.

Previous experience applying machine learning and optimization techniques within marketplace or e-commerce environments is highly valued and considered a strong advantage.

Practical notes

Please be aware that We are committed to transparency in pay ranges and encourage all qualified candidates to apply without hesitation.