Staff Machine Learning Engineer, Instacart

• 7+ years of production ML experience, with a strong record of successful multi-project initiatives
• Proficiency in Python and either TensorFlow or PyTorch
• A solid foundation in testing, systems observability, and problem-solving
• Exceptional communication skills and the ability to lead and collaborate with a diverse set of functions across teams (SWEs, PMs, Product Engineers, etc.)

Desirable

• We are looking for a highly motivated Staff Machine Learning Software Engineer to join our team
• You'll be instrumental in building our next generation platforms for understanding, observing, and predicting inventory levels in real time – think: platforms that provide the precision and depth of a warehouse but scaled to every local store
• In this role you will bring a systems-thinking approach to leading and establishing strategic technical investments and you’ll build a culture of best practices for machine learning
• In close collaboration with software engineers, product leads, and data scientists, you will bring relevant advanced technologies to the team while driving new product innovation
• The inventory intelligence team is responsible for understanding exactly what is on store shelves at all times
• Inventory estimates drive some of the most important products at instacart from search to logistics
• This high performance team is like a startup within the company, driving the end-to-end shelf data supply chain including ingestion of data sources from partners to actively collecting novel inventory observations to model development and product integration
• Own end-to-end outcomes that require thinking across multiple models, data sources, and dynamical systems
• Develop strategic roadmap for modeling inventory dynamics in both high and low observation-density regimes
• Make appropriate technology choices depending on the maturity and nature of each problem
• Collaborate across teams to foster a unified approach to development, facilitating consensus and driving effective outcomes
• Directly contribute and execute on some projects, from inception to deployment and maintenance
• Supercharge and mentor teammates, introduce relevant advanced technologies, and build a culture of best practices for machine learning