Senior Machine Learning Engineer, Digital Twin Platform

Instacart is a grocery technology company building services that connect customers with groceries and household goods. The Senior Machine Learning Engineer will develop and deploy models for real-time inventory and shelf-stocking intelligence, own the full machine learning lifecycle, and help evolve the Digital Twin Platform in collaboration with engineering, computer vision, product, and data science teams.

Responsibilities:

• Design, develop, and deploy machine learning models that power real-time understanding of in-store inventory levels and shelf stocking dynamics across thousands of retail locations at scale
• Own the full ML lifecycle — from problem framing and data exploration through model training, evaluation, and production deployment — with a focus on quality, reliability, and measurable business impact
• Collaborate cross-functionally with software engineers, computer vision engineers, data scientists, and product leads to bring cutting-edge technologies to the team and drive new product innovation
• Contribute to building and evolving the core infrastructure of the Digital Twin Platform, including systems that ingest data from retail partners and actively collect novel inventory observations to feed the modeling pipeline
• Help define the technical direction of an expanding modeling practice on a high-performance team that operates with startup speed — expect ambiguity, changing priorities, and the opportunity to make a significant mark on a problem space that is core to Instacart's business

Requirements:

• 5+ years of experience developing and deploying machine learning models in production environments
• Strong proficiency in Python and experience with ML frameworks such as TensorFlow, PyTorch, or scikit-learn
• Demonstrated experience with large-scale data pipelines and working with structured and unstructured data at scale
• Experience with cloud infrastructure (AWS, GCP, or Azure) and familiarity with ML platform tooling for model training, versioning, and serving
• Bachelor's degree or higher in Computer Science, Machine Learning, Statistics, or a related technical field, or equivalent practical experience
• Experience working on computer vision, inventory forecasting, demand sensing, or related spatial/temporal modeling problems
• Familiarity with real-time inference systems and the architectural considerations of serving ML models in low-latency, high-throughput environments
• Prior experience in a fast-paced, cross-functional environment where you have independently driven projects from conception through production with limited oversight
• Exposure to retail, supply chain, or e-commerce domains and an understanding of how inventory data flows and is consumed in those contexts
• Experience collaborating closely with computer vision teams or incorporating vision-based signals into broader ML systems