Machine Learning Engineer, Reinforcement Learning

DoorDash

San Francisco, CA, US
I4: $137,100 - $201,600; i5: $167,800 - $246,800; ...
On-site
Reinforcement learning expertise
Production ml solutions
Python programming skills
Develop production machine learning solutions for reinforcement learning problems such as multi-armed bandits, contextual bandits, Markov Decision Processes (MDPs), and deep reinforcement learning

Job Summary

  • Develop production machine learning solutions for reinforcement learning problems such as multi-armed bandits, contextual bandits, Markov Decision Processes (MDPs), and deep reinforcement learning.
  • Collaborate with cross-functional leaders across engineering, product, and business strategy to help shape a product roadmap driven by machine learning, accelerating the growth of a multi-billion-dollar retail delivery ecosystem.
  • DoorDash offers a comprehensive benefits package including a 401(k) plan with employer matching, 16 weeks of paid parental leave, wellness benefits, and premium healthcare.

Matching Summary

Develop production machine learning solutions for reinforcement learning problems such as multi-armed bandits, contextual bandits, Markov Decision Processes (MDPs), and deep reinforcement learning.

Salary

I4: $137,100 - $201,600; I5: $167,800 - $246,800; I6: $203,500 - $299,300

Skills & Requirements

Must-have

  • Reinforcement learning expertise
  • Production ML solutions
  • Python programming skills
  • ML/RL frameworks (PyTorch, TensorFlow, RLlib)
  • Sequential decision making tasks

Nice-to-have

  • Cross-functional collaboration
  • Flexible experimentation culture
  • Causal inference familiarity
  • Continuous improvement mindset

Key Requirements

  • Industry experience shipping ML solutions to production
  • Deep expertise in applied reinforcement learning
  • M.S. or PhD in quantitative field is a plus
  • Must be located near engineering hubs

Work Rights

Not specified

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