Senior ML Engineer, Fauna

Description

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

About the team
Fauna Robotics, an Amazon company, is building capable, safe, and genuinely delightful robots for everyday life. Our goal is simple: make robots people actually want to live and interact with in everyday human spaces.
We believe that future won’t arrive until building for robotics becomes far more accessible. Today, too much effort is spent reinventing the fundamentals. We’re changing that by developing tightly integrated hardware and software systems that make it faster, safer, and more intuitive to create real-world robotic products.
Our work spans the full stack: mechanical design, control systems, dynamic modeling, and intelligent software. The focus is not just functionality, but experience. We’re building robots that feel responsive, expressive, and genuinely useful.
At Fauna, you’ll work at the frontier of this space, helping define how robots move, manipulate, and interact with people in natural environments. It’s an opportunity to solve hard problems across hardware and software with a team focused on making robotics accessible and joyful to build.
If you care about making robotics real for everyone and building systems that are as delightful as they are capable, we’re interested in hearing from you.

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
- 5 years of non-internship professional experience in applied ML engineering with direct model training responsibilities
- Master’s or PhD in Computer Science, Machine Learning, Robotics, or related field, or equivalent practical experience
- Strong software engineering fundamentals in Python
- Deep proficiency with machine learning toolkits (PyTorch, etc.) with experience designing, training, and debugging non-trivial model architectures
- Track record of collaboration with research scientists in fast-paced environments

Preferred Qualifications

- Hands-on experience with reinforcement learning or imitation learning
- Proficiency with containerization (Docker) and orchestration (Kubernetes).
- Experience with model optimization for edge deployment (quantization, pruning, TensorRT, ONNX)
- Experience with physics simulation environments (Isaac Lab, MuJoCo, PyBullet, or equivalent)
- Experience with ML infrastructure tools (e.g., MLflow, Weights & Biases, Kubeflow, Ray).

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

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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t 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 https://amazon.jobs/en/benefits.