• You will help design and build end-to-end machine learning solutions. • You will be working in small and cross-functional product teams, with great opportunities for growth and ownership of projects. • You will be an active member of an internal community, including economists, data scientists, operations research scientists and machine learning engineers, sharing learnings, best practices and research across many domains. • You will develop high impact solutions to support Instacart's ambitious growth plans. • You will work closely with engineers, product managers, other teams, and both internal and external stakeholders, owning a large part of the process from problem understanding to recommending a solution and testing it in controlled experiments. • You will have the freedom to suggest and drive organization-wide initiatives.

• Build and maintain scalable machine learning solutions in production • Train and validate both deep learning-based and statistical-based models considering use-case, complexity, performance, and robustness • Demonstrate end-to-end understanding of applications and develop a deep understanding of the “why” behind our models & systems • Partner with product managers, tech leads, and stakeholders to analyze business problems, clarify requirements and define the scope of the systems needed • Work closely with data platform teams to build robust scalable batch and realtime data pipelines • Collaborate with software engineers, build tools to enhance productivity and to ship and maintain ML models • Drive high engineering standards on the team through mentoring and knowledge sharing • Uphold engineering best practices around code reviews, automated testing and monitoring

• looking for a year-round intern (summer intern is also acceptable) • work on projects developing learning-based analytics • cyber-attack-resilient control strategies and optimizations for power distribution systems • conducting literature review • identifying gaps and summarizing new research opportunities • conduct research work independently • collaborate with project PI and other researchers from the project team

• Improve our existing machine learning systems using your core coding skills and ML knowledge • Take end to end ownership of machine learning systems - from data pipelines, feature engineering, candidate extraction, model training, as well as integration into our production systems • Apply state-of-the-art machine learning algorithms at scale and serving for next-generation targeting and bidding products that directly impact the company’s top line metrics • Collaborate with ML platform and product engineers to build scalable and efficient machine learning systems in the production environment • Work with product and business teams on new innovative features for ad targeting and bidding to optimize advertisement performance • Identify new opportunities to apply machine learning to different parts of the Ads product to drive value for our users and advertisers