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DoorDash is looking to develop modern growth and personalization models that power their growing retail and grocery business.

Requirements

• Expertise in applied ML for Causal Inference and Recommendation Systems - both classical and deep learning based
• Machine learning background in Python; experience with PyTorch or TensorFlow preferred
• Additional familiarity with explore/exploit/MAB algorithms & LLMs is a plus
• 5+ years of industry experience developing machine learning models with business impact, and shipping ML solutions to production
• M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field

Responsibilities

• Develop production machine learning solutions to build a world class personalized shopping experience for a diverse and expanding retail space
• Partner with engineering and product leaders to help shape the product roadmap applying ML
• Mentor junior team members, and lead cross functional pods to create collective impact

Other

• Ability to communicate technical details to nontechnical stakeholders
• Desire for impact with a growth-minded and collaborative mindset
• You keep the mission in mind, take ideas and help them grow using data and rigorous testing, show evidence of progress and then double down
• M.S., or PhD. in Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field
• 401(k) plan with employer matching, paid time off and paid sick leave in compliance with applicable laws
• 16 weeks of paid parental leave, a wellness benefit, and a commuter benefit match
• Medical, dental, and vision benefits, 11 paid holidays, disability and basic life insurance, family-forming assistance, and a mental health program