Machine Learning Engineer, Reinforcement Learning

<div class="content-intro"><p><img style="display: none; max-width: 100%;" src="https://click.appcast.io/greenhouse-te8/a31.png?ent=34e=22630t=1701374353806" width="1px"> <img style="display: none; max-width: 100%;" src="https://track.jobadx.com/v1/i.gif?utm_pixel=224e990b-8ff4-4287-8d5d-2ff09647f181utm_ptz=ESTutm_rqt=track" alt="" width="1"></p></div><h2><strong>About the Team</strong></h2> <p>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. </p> <h2><strong>About the Role</strong></h2> <p>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.</p> <h2><strong>You’re excited about this opportunity because you will…</strong></h2> <ul> <li>Develop production machine learning solutions to solve<strong> reinforcement learning </strong>problems such as multi-armed bandits, contextual bandits, Markov Decision Processes (MDPs), and deep reinforcement learning (e.g., DQN, actor–critic methods).</li> <li>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.</li> <li>Explore and harness diverse data sources, leveraging intuitive models and fostering a culture of flexible experimentation. Your goal will be to continuously improve the shopping and dashing experiences, delivering solutions that are not only effective but also scalable and user-centric.</li> <li>Drive impact and enjoy ample room for both personal and professional growth. This includes opportunities for deep technical development and leadership as you work within a growing team that is actively unlocking new markets for the company.</li> <li>Innovate and experiment with cutting-edge technologies and methodologies in AI and ML. You’ll have the freedom to explore emerging technologies, test new ideas, and drive technical innovation in the reinforcement learning space, directly shaping the future of our retail and delivery solutions.</li> </ul> <h2><strong>We’re excited about you because you have…</strong></h2> <ul> <li>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.</li> <li>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.</li> <li>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.</li> <li>You must be located near one of our engineering hubs which includes: San Francisco, Sunnyvale, Los Angeles, Seattle, and New York</li> <li>M.S., or PhD. in Machine Learning/Reinforcement Learning, Statisti ... (truncated, view full listing at source)