Applied Scientist, Safe RL, Robotics, SAF Lab

We are seeking an Applied Scientist to join the SAF this role you will lead the effort in safe reinforcement learning (RL) including the development of legged locomotion algorithms that internalize safety and are deployable on physical hardwareenabling highly dynamic robots to walk run avoid collisions and recover from disturbances with agility and robustness. You will develop RL architectures that interface with physics-based models (for dynamic retargeting and reward shaping) internalize safety constraints in training sim-to-real transfer and interface with safety filters at run-time. Therefore your work will sit at the intersection of safety-critical control and learning and you will collaborate with others in the SAF Lab and Amazon working on perception planning whole-body and safety-critical control. This is an opportunity to shape the foundations of safe learning on emerging platforms that will remove bottlenecks to deployment and enable these robots to safely operate around humans.

Key job responsibilities
Collaborate with product teams and science leaders to set a science roadmap (with eventual impact on real robots).
Design train and deploy reinforcement learning (RL) policies for dynamic legged locomotion including walking running stair climbing and fall recovery on physical robots
Develop sim-to-real transfer pipelines that produce policies robust to the reality gap including domain randomization system identification and adaptive strategies
Integrate control-based methods with RL as inputs to the RL (dynamic retargeting and control-guided rewards) in training (internalizing safety constraints in training) and as the RL feeds into safety layers and whole-body control
Develop and maintain large-scale training infrastructure for locomotion policy learning including physics simulation environments domain randomization and GPU parallelization
Investigate the distillation of locomotion policies integration with whole-body control foundation models VLAs world models perception and full-stack autonomy
Evaluate policy performance rigorously through simulation benchmarks hardware experiments and failure-mode analysis
Publish research at top-tier robotics and ML venues and contribute to Amazons scientific reputation in advanced robotics
Collaborate with perception and planning teams to enable terrain-aware and goal-conditioned locomotion behaviors


A day in the life
Amazon offers a full range of benefits that support you and eligible family members including domestic partners and their children. Benefits can vary by location the number of regularly scheduled hours you work length of employment and job status such as seasonal or temporary employment. The benefits that generally apply to regular full-time employees include:

1. Medical Dental and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly wed still love to hear from you! At Amazon we value people with unique backgrounds experiences and skillsets. If youre passionate about this role and want to make an impact on a global scale please apply!

About the team
Work with the inventor of control barrier functions in the Safe Autonomy Frontiers (SAF) Lab. The first industry research lab in safe autonomy developing a universal safety layer for the next generation of robotic systems: mobile robots manipulators mobile manipulators and future platforms with dynamic stability. You will push the frontiers of performant safety for highly dynamic robots: CBF theory integrated with perception and learning evaluated on next-generation robots. Your work will underpin robots operating alongside people at Amazons unprecedented scale.

- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- PhD in Computer Science Robotics Mechanical Engineer Electrical Engineering or a related field with a focus on reinforcement learning robot learning or control
- Experience applying RL to physical robotic systems (beyond simulation-only work) including demonstrated expertise in sim-to-real transfer on dynamically stable robots
- Strong understanding of legged robot dynamics contact mechanics and whole-body control fundamentals
- Proficiency in Python and deep learning frameworks (e.g. PyTorch JAX) with experience building custom RL training pipelines
- Experience with physics simulators for robotics (e.g. Isaac Gym/Sim MuJoCo PyBullet)

- Experience in professional software development
- Knowledge of safety-critical control including control barrier functions and safety filters.
- Familiarity with safety-constrained RL (e.g. constrained MDPs Lagrangian methods shielding CBF-based policy filtering)
- Experience with model-based control (MPC whole-body QP controllers operational space control) and how to interface these methods with RL
- Knowledge of stability theory (Lyapunov methods orbital stability) as it applies to periodic gaits
- Experience with hierarchical RL skill composition distillation and multi-task policy architectures for locomotion
- Familiarity with real-time deployment constraints (latency budgets onboard compute limitations control-loop frequencies)
- Experience building or contributing to large-scale RL training infrastructure (distributed training GPU clusters)
- Strong communication skills and ability to work across disciplinary boundaries (ML controls mechanical engineering)

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees supervisors and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees supervisors and staff to ensure exceptional customer service; and follow all federal state and local laws and Company policies. Criminal history may have a direct adverse and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above as well as the abilities to adhere to company policies exercise sound judgment effectively manage stress and work safely and respectfully with others exhibit trustworthiness and professionalism and safeguard business operations and the Companys reputation. Pursuant to the Los Angeles County Fair Chance Ordinance we will consider for employment qualified applicants with arrest and conviction records.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at CA PASADENA - 142800.00 - 193200.00 USD annually