Senior Staff Machine Learning Engineer, Consumer

DoorDash DoorDash · Consumer · Sunnyvale, CA · 346 Consumer Engineering

Senior Staff ML Engineer focused on setting personalization strategy for the consumer shopping journey, implementing ML solutions for search relevance, and modernizing recommendation systems using AI. The role involves driving engineering vision, mentoring teams, and partnering on agentic commerce initiatives. Requires deep expertise in deep learning, fine-tuning, and optimizing LLM systems, with a strong command of production ML and experience shipping ML solutions.

What you'd actually do

  1. Drive the engineering vision, strategy, and execution for an organization of 150+
  2. Grow, build, and nurture impactful business-focused product engineering teams. Scale the team by developing leaders internally and attracting world-class talent
  3. Mentor and guide a fast-growing organization in setting the right architectural patterns, working with various vendors in the space, and making judicious investments in the right areas anticipating what the company needs a few years down the road.
  4. Partner with Business, Product, and other Engineering teams to transform DoorDash from local commerce to agentic commerce

Skills

Required

  • B.S. or M.S. in Computer Science or equivalent.
  • 10+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
  • Proficiency in using AI coding tools (e.g., Claude Code) in the full software development lifecycle, including designing, generating code, testing, monitoring and releasing software
  • Proven ability to drive multi-quarter technical roadmaps as a technical lead, with clear ownership of architectural decisions.
  • Deep expertise in deep learning, and fine-tuning.
  • Hands-on experience optimizing LLM systems (e.g., fine-tuning, advanced prompting strategies, structuring JSON/tool-calling outputs).
  • Strong technical intuition paired with the ability to influence and align cross-functional stakeholders.

Nice to have

  • Humility and growth mindset, leading through expertise and collaboration, not hierarchy.

What the JD emphasized

  • 10+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production.
  • Deep expertise in deep learning, and fine-tuning.
  • Hands-on experience optimizing LLM systems (e.g., fine-tuning, advanced prompting strategies, structuring JSON/tool-calling outputs).

Other signals

  • modernize recommendation system leveraging AI
  • implement new ML solutions to make the consumer search experience more relevant
  • optimize LLM systems