Senior Applied Scientist

Amazon
SAN FRANCISCO, CA, USA / Sunnyvale, CA, USA2026-04-17ONSITE

About the job

Amazon is seeking exceptional talent to help develop the next generation of advanced robotics systems that will transform automation at Amazon's scale. We're building revolutionary robotic systems that combine innovative AI, sophisticated control systems, and advanced mechanical design to create adaptable automation solutions capable of working safely alongside humans in dynamic environments. This is a unique opportunity to shape the future of robotics and automation at unprecedented scale, working with world-class teams pushing the boundaries of what's possible in robotic manipulation, locomotion, and human-robot interaction. This role presents an opportunity to shape the future of robotics through innovative applications of deep learning and large language models.

Responsibilities

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.

Qualifications

Minimum

3+ years of building machine learning models for business application experience

PhD, or Master's degree and 6+ years of applied research experience

Experience programming in Java, C++, Python or related language

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

Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

Experience with large scale distributed systems such as Hadoop, Spark etc.

Experience using Unix/Linux

Experience in professional software development