As an Applied Scientist, you will develop and improve machine learning systems that help robots perceive, reason, and act in real-world environments. You will leverage state-of-the-art models (open source and internal research), evaluate them on representative tasks, and adapt/optimize them to meet robustness, safety, and performance needs. You will invent new algorithms where gaps exist. You'll collaborate closely with research, controls, hardware, and product-facing teams, and your outputs will be used by downstream teams to further customize and deploy on specific robot embodiments.
Key job responsibilities
As an Applied Scientist in the Foundations Model team, you will:
- Leverage state-of-the-art models for targeted tasks, environments, and robot embodiments through fine-tuning and optimization.
- Execute rapid, rigorous experimentation with reproducible results and solid engineering practices, closing the gap between sim and real environments.
- Build and run capability evaluations/benchmarks to clearly profile performance, generalization, and failure modes.
- Contribute to the data and training workflow: collection/curation, dataset quality/provenance, and repeatable training recipes.
- Write clean, maintainable, well commented and documented code, contribute to training infrastructure, create tools for model evaluation and testing, and implement necessary APIs
- Stay current with latest developments in foundation models and robotics, assist in literature reviews and research documentation, prepare technical reports and presentations, and contribute to research discussions and brainstorming sessions.
- Work closely with senior scientists, engineers, and leaders across multiple teams, participate in knowledge sharing, support integration efforts with robotics hardware teams, and help document best practices and methodologies.
BASIC QUALIFICATIONS
- 2+ years of building models for business application experience
- Knowledge of programming languages such as C/C++, Python, Java or Perl
- PhD, or Master's + 4+ years building ML models/algorithms in applied settings
- 2+ years hands-on experience in deep learning with strength in at least one: computer vision, multimodal models, imitation learning / RL for robotics, or human-robot interaction
- Ability to design rigorous experiments, analyze results, and iterate quickly with reproducible baselines
- Demonstrated technical contributions (e.g., publications, patents, open-source, or impactful internal systems)
PREFERRED QUALIFICATIONS
- Experience using Unix/Linux
- Experience in professional software development
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, CA, SAN FRANCISCO - 171,600.00 - 222,200.00 USD annually
USA, CA, Sunnyvale - 171,600.00 - 222,200.00 USD annually
