Member of Technical Staff - Engineer, RL and Control

Position Summary You will help build and refine the learned controllers that give our humanoid robots capable whole-body motion, and help get them working reliably on real hardware. Working alongside senior RL and controls engineers, you'll train and tune policies, run experiments in large-scale simulation, and take an active role in bringing controllers up on physical robots and closing the sim-to-real gap. This is a hands-on role for an engineer who wants to grow their depth in reinforcement learning and control while contributing directly to robots that work in the real world-implementing, tuning, evaluating, and debugging the controllers that others help architect, and taking increasing ownership over time. Core Responsibilities Policy Training & Tuning: Train, tune, and evaluate reinforcement learning policies for whole-body control tasks such as balance, locomotion, and manipulation. Simulation Experiments: Set up and run experiments in large-scale simulation, analyze results, and iterate quickly on policy designs. Sim-to-Real Support: Contribute to the sim-to-real pipeline—domain randomization, system identification, and the iterative work of making policies transfer to hardware. Real-Robot Bring-Up: Help bring controllers up on physical robots, run experiments, and debug behavior in the real world. Evaluation & Tooling: Build and improve tools for evaluating controller performance in simulation and on hardware. Collaboration: Work closely with senior RL, controls, and hardware engineers, taking direction on harder design decisions while owning your own workstreams end-to-end. Required Qualifications Candidates should have strong foundations in at least one of the following RL: Solid working knowledge of reinforcement learning — including policy optimization methods (e.g., PPO), reward shaping, domain randomization, demonstration-guided RL — with hands-on experience training policies for continuous control tasks such as locomotion or manipulation. Model-Based Control: Solid working knowledge of optimization-based control, such as trajectory optimization, MPC, QP-based control, inverse kinematics and differential IK. Foundational understanding of robot modeling: dynamics, kinematics,, coordinate frames, and control fundamentals (for instance PID control, stiffness/impedance control). Real-Robot Experience: Experience working with physical robots—bringing up, testing, or debugging controllers on real hardware. Software Engineering: Strong Python skills and the ability to write clean, testable code; working C++ ability or willingness to grow it. Simulation: Experience with setting up, implementing and, and running experiments in physics simulation for robotics or RL, for instance in Drake, Mujoco, etc. Curiosity & Drive: Eagerness to learn, iterate quickly, and take on increasing ownership. Preferred Qualifications Experience with whole-body control, locomotion, or manipulation on legged or humanoid robots. Familiarity with sim-to-real techniques and their practical challenges. Exposure to classical/model-based control (MPC, QP controllers, trajectory optimization). Experience with ML experiment-tracking and training workflows. Experience with state-of-the-art machine learning and GPU programming frameworks, such as pytorch, WARP, JAX. Coursework, projects, or publications in robotics, RL, or control. Walden Robotics offers a competitive total compensation program, including salary, annual cash bonus, company equity, company-subsidized insurance programs, 401(k) with company match, flexible PTO, daily lunch, and other benefits. The pay ranges noted on our posts are for salary only. Walden Robotics is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request to View email address on click.appcast.io. Walden Robotics participates in E-Verify. If you receive an offer of employment from Walden, you will need to go through the E-Verify process of digital verification of your employment authorization documents as provided on the Form I-9. Participation in E-Verify does not limit your right to work and verification will only be completed after you become At Walden Robotics, we envision a world where general-purpose robots dramatically improve the quality of life for all people—supporting us at home, at work, in factories, on farms, and beyond. To accomplish this, we are building a team of exceptional professionals who combine world-class technical skills with creative vision, grounded in humility and collaboration. #J-18808-Ljbffr Walden Robotics