• Train, fine-tune, and evaluate machine learning models on real-world workflow and behavioral data • Build predictive models for task outcomes, productivity trends, capacity forecasting, and workflow optimization • Fine-tune large models and foundation models for domain-specific prediction, classification, and embedding tasks • Design and maintain feature pipelines, training loops, and evaluation frameworks • Work with engineers and product teams to integrate trained models into production systems • Monitor model performance and iterate using offline evaluation and live data feedback

• Develop software applications with a strong focus on machine learning • Train deep learning models using PyTorch and Transformers and experiment with (new) techniques to reduce their memory footprint, speed them up, or increase their accuracy • Deploy software applications, including deep learning models, in production, using AWS and Greenhouse’s internal tools • Partner with other members of the R&D team to uplevel their comfort and familiarity with shipping Machine Learning features • Help set vision and strategy for AI within our product suite • Develop applications that are compliant with our AI policies that prioritize privacy, security, ethical concerns, and best practices while handling data • Contribute to and build all phases of the AI system lifecycle from ideation, model development, testing, evaluation, improvements and monitoring

• Own well-scoped ML components or models: You will take ownership of specific components, executing on defined problems with guidance • Train and deploy models using established patterns, and ship models to production following existing tooling and standards • Monitor and debug models with help from senior engineers, and work to improve model performance incrementally • Implement AI governance, privacy, and security requirements as defined • Collaborate within the team and with partner functions, while communicating progress, risks, and blockers clearly

• 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.