Machine Learning Engineer, Reinforcement Learning

Industry experience developing machine learning models with business impact, and shipping ML solutions to production. You have successfully shipped ML solutions to production and understand the nuances of transitioning models from development to real-world environments.

Deep expertise in applied reinforcement learning, with hands-on experience solving challenging RL-related problems and implementing solutions that drive customer value. Your knowledge extends to solving complex sequential decision making tasks.

Strong machine learning and programming skills, particularly in Python, with experience in key ML/RL frameworks such as PyTorch, TensorFlow, RLlib, TorchRL, etc. You’re able to implement scalable models and optimize performance for production systems.

You must be located near one of our engineering hubs which includes: San Francisco, Sunnyvale, Los Angeles, Seattle, and New York

M.S., or PhD. in Machine Learning/Reinforcement Learning, Statistics, Computer Science, Math, Operations Research, Physics, Economics, or other quantitative field is a plus

Familiarity with causal inference and experimentation techniques, enabling you to design and evaluate experiments that validate the effectiveness of ML models and ensure the product’s continuous improvement.

We’re looking for a passionate Applied Machine Learning expert to join our team. As a Reinforcement Learning expert, you’ll be conceptualizing, designing, implementing, and validating algorithmic improvements to the reinforcement learning system at the heart of our fast-growing grocery and retail delivery business.  You will use our robust data and machine learning infrastructure to implement new ML solutions to make our product selection and inventory information more accurate and real time,  as well as help Dasher efficiency. We’re looking for someone with a command of production-level machine learning and experience with solving end-user problems who enjoys collaborating with multidisciplinary teams.

Develop production machine learning solutions to solve

reinforcement learning

problems such as multi-armed bandits, contextual bandits, Markov Decision Processes (MDPs), and deep reinforcement learning (e.g., DQN, actor–critic methods).

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.

Come help us build the world's most reliable local e-commerce platform for on-demand last-mile grocery and retail delivery! We're looking for an experienced senior machine learning engineer to help us develop the cutting-edge reinforcement learning models that power DoorDash's growing grocery and retail business.