Postdoctoral Scholar SAF Lab, Compass

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

We are seeking a Postdoctoral Scholar to join the SAF this role you will perform research around safe autonomy on highly dynamic robots with a special focus on loco-manipulation and dynamically stable robots. This includes but is not limited to underlying theory of control barrier functions (CBFs) that enables robust and performant safety on hardware safe reinforcement learning for agile and robust whole-body control layered safety filters that interface with learning modules and the synthesis of CBFs from perception data and semantic information. You will push the boundaries of safe autonomy and validate your discoveries experimentally on the next generation of robotic platforms.

The SAF lab provides a unique opportunity to collaborate with the inventor of CBFs top scientists and engineers at Amazon developing the next generation of safe autonomy while also establishing strong connections with top academic research labs. Your research in the SAF lab will lay the foundations of safe learning on complex robots removing bottlenecks to deployment and enable them to safely operate around humans.


Key job responsibilities
In this role you will:
Push forward the fundamental science of safe autonomy. This can be from a variety of perspectives: theoretic contributions integration with learning or synthesis from perception. Especially valuable are methods that bridge these different domains.
Develop the simulation and evaluation pipelines needed to run complex and large-scale validation of methods developed in high fidelity simulation environments.
Develop sim-to-real transfer pipelines that enable the deployment of simulation-based methods (controllers policies) on hardware.
Deploy the methods developed on hardware with a focus on dynamically stable robots. Validate the underlying science developed in practice and identify gaps between the science and practice to drive innovation in research.
Publish research at top-tier robotics control and ML venues and contribute to Amazons scientific reputation in advanced robotics
Collaborate with product teams and science leaders to set a science roadmap (with eventual impact on real robots).


A day in the life
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PhD in Computer Science Robotics Control Mechanical Engineer Electrical Engineering or a related field with a focus on control learning and/or robotics.
Deep understanding of safety-critical control including control barrier functions and safety filters.
Proficiency in C and Python with experience implementing control algorithms and/or learning policies
Experience with physics simulators for robotics (e.g. Isaac Gym/Sim MuJoCo PyBullet)
Experience validating on physical robotic hardware (not simulation-only)
Track record of publications at top-tier venues in control and robotics (e.g. RSS ICRA IROS CDC CoRL NeurIPS ICLR L-CSS RAL TRO TAC)


Understanding of locomotion reduced order models layered control architectures nonlinear control reachability methods and whole-body control
Knowledge of learning-based approaches to robotics (e.g. reinforcement learning diffusion VLAs VLMs world models.)
Exposure to learning-based approaches for CBF synthesis (e.g. neural CBFs data-driven barrier functions) and the integration of CBFs into learning (e.g. CBF-RL)
Understanding of control systems engineering with a specific focus on layered architecture used in robotic systems (high level planning mid-level trajectory generation and low-level feedback control)
Experience with perception on robotic systems (e.g. depth camera and LiDAR based sensing modalities sensor fusion semantic tagging).
Familiarity with Hamilton-Jacobi reachability analysis and its relationship to CBF-based approaches
Knowledge of 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/or simulation-based predictive control (MPPI)
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.

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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 - 136000.00 - 184000.00 USD annually