Senior Machine Learning Engineer

Instacart
$173,000 - $218,500Remote

About The Position

We are looking for a Senior Machine Learning Engineer with a strong Operations Research background to join the Service Availability & Routing team within Instacart's Logistics organization. In this role, you will work at the intersection of combinatorial optimization, mathematical programming, and AI to solve high-impact problems in the fulfillment space — including order batching, shopper routing, service availability prediction, and real-time assignment. You'll partner closely with engineering, product, and data science to ship models and algorithms that directly influence Instacart's profitability and shopper experience at scale. The Logistics & ML group is responsible for the intelligence and execution behind Instacart’s fulfillment system. The team optimizes a multi-sided marketplace to ensure customers get their orders on-time and in high quality, shoppers get efficient and fulfilling work, and retailers and consumer brands get reasonable business. The team tackles hard problems in a variety of spaces, such as matching, pricing, and geospatial, as well as foundational problems executing on a high throughput system with dynamic data.

Requirements

  • Have a graduate degree (masters or PhD) in Operations Research or Industrial Engineering
  • 3+ years of industry experience using machine learning to solve real-world problems with large datasets
  • Have strong programming skills in Python and fluency in data manipulation (SQL, Pandas) and Machine Learning (scikit-learn, XGBoost, Keras/Tensorflow) tools
  • Have strong analytical skills and problem-solving ability
  • Are a strong communicator who can collaborate with diverse stakeholders across all levels

Nice To Haves

  • Knowledge of deep learning frameworks and methodologies
  • Experience in applying machine learning and optimization techniques to solve marketplace problems

Responsibilities

  • Design, develop, and deploy machine learning solutions to tackle practical challenges in the marketplace.
  • Collaborate closely with product managers, data scientists, and backend engineers to deeply understand business needs and create impactful ML applications.
  • Actively engage with diverse stakeholders to ensure that solutions are well-integrated and aligned with business goals.
  • Push the envelope on our operational efficiency by continually refining and advancing our algorithms and models.
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