We are seeking a Machine Learning Engineer to work directly alongside our research scientists to train, evaluate, and deploy the models that make our robots move, perceive, and act in the real world. This is a hands-on ML role: you will train policies, debug convergence, run experiments in simulation, and push models onto hardware - not just build the pipes around them.
You'll bring deep expertise in reinforcement learning, computer vision, and supervised learning applied to robotics and embodied systems. You also need to think seriously about training infrastructure - managing GPU clusters, optimizing distributed training, and shipping models to edge devices - but the core of this role is getting in the loop with scientists and making models work.
Key job responsibilities
Train and iterate on neural network policies for locomotion, manipulation, navigation, and perception using reinforcement and supervised learning
Design and run experiments in simulation (Isaac Lab, MuJoCo, or similar) and transfer results to physical hardware
Debug training runs end-to-end: diagnosing convergence failures, reward shaping issues, data quality problems, and sim-to-real gaps
Optimize models for deployment on edge hardware (NVIDIA Jetson) with strict latency and memory constraints
Build and maintain MLOps infrastructure: experiment tracking, model versioning, evaluation pipelines, and reproducible training workflows
BASIC QUALIFICATIONS
- 5+ years of non-internship professional software development experience
- 5+ years of programming with at least one software programming language experience
- 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience as a mentor, tech lead or leading an engineering team
- Bachelor's degree or above in robotics, mechanical/mechatronics engineering, systems engineering or related field
- Knowledge of data structures, algorithm design, statistics, and system design
- Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
- Experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation
PREFERRED QUALIFICATIONS
- Experience in robotics design, automation systems development, control systems design, or related product development
- Experience with training and deploying machine learning systems to solve large-scale optimizations, or experience in development or technical support
- Experience mentoring or training the engineering community on complex technical issues
- Track record of delivering developer-facing products with robust SDKs and fault-tolerant distributed systems.
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 https://amazon.jobs/en/benefits.
USA, NY, New York - 184,900.00 - 250,200.00 USD annually
