Staff ML Engineer - Personalization for Retail Growth

DoorDash; California (MO); Hybrid; USD 137,000 - 247,000; Full time

Benefits offered by this job

Equity grants

Comprehensive benefits

Job summary

DoorDash is seeking an experienced Staff Machine Learning Engineer to design, implement, and validate production ML improvements for growth and personalization in our grocery and retail delivery spaces.

You will work with data infrastructure to deploy ML solutions that enhance consumer search relevance and experience across categories, reporting to the Personalization team manager. Hybrid in-office and remote work is expected.

Qualifications

• 8+ years of industry experience developing ML models with business impact and shipping ML solutions to production.
• Proficiency with AI coding tools in the full software development lifecycle, including design, generation, testing, monitoring and releasing software.
• M.S., or PhD in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or related quantitative field.
• Expertise in applied ML for Causal Inference and Recommendation Systems; familiarity with explore/exploit/MAB and LLMs is a plus.
• Machine learning background in Python; PyTorch or TensorFlow preferred.
• Ability to communicate technical details to nontechnical stakeholders.
• Growth-minded, collaborative mindset with a focus on impact.

Responsibilities

• Develop production ML solutions to build a world-class personalized shopping experience for a growing retail space.
• Collaborate with engineering and product leaders to shape the product roadmap using ML.
• Mentor junior team members and lead cross-functional pods to drive impact.

Skills

Production ML

Causal Inference

Recommendation Systems

Python (ML)

LLMs

Education

M.S./PhD in quantitative field

Tools

Claude Code

Codex

Cursor

PyTorch

TensorFlow

Job description

DoorDash is seeking an experienced Staff Machine Learning Engineer to design, implement, and validate production ML improvements for growth and personalization in our grocery and retail delivery spaces.

You will work with data infrastructure to deploy ML solutions that enhance consumer search relevance and experience across categories, reporting to the Personalization team manager. Hybrid in-office and remote work is expected.