Staff Software Engineer, Machine Learning - Personalization

DoorDash is seeking a Staff Machine Learning Engineer for their Personalization team to develop modern growth and personalization models for their growing retail and grocery business. The role involves conceptualizing, designing, implementing, and validating algorithmic improvements to enhance the consumer search experience across grocery, convenience, and other retail categories.

Key Responsibilities: • Develop production machine learning solutions for a world-class personalized shopping experience • Partner with engineering and product leaders to shape the product roadmap applying ML • Mentor junior team members and lead cross-functional pods

Requirements: • 8+ years of industry experience developing ML models with business impact and shipping ML solutions to production • M.S. or Ph.D. in a quantitative field (Statistics, Computer Science, Math, Operations Research, Physics, Economics) • Expertise in applied ML for Causal Inference and Recommendation Systems • Machine learning background in Python; experience with PyTorch or TensorFlow preferred • Strong communication skills and ability to explain technical details to non-technical stakeholders • Growth-minded and collaborative mindset with a focus on impact

The role offers competitive compensation, equity grants, and comprehensive benefits. DoorDash values diversity and inclusion, encouraging applications from candidates of all backgrounds.

This hybrid position requires some time in-office and some remote work, reporting to the engineering manager on the Personalization team. The company is committed to building a reliable on-demand logistics engine for last-mile retail delivery and seeks passionate individuals to join their innovative team.