Applied Scientist, Robotics Foundations & AI

Amazon.com Services LLC; Sunnyvale (CA); On-site; USD 160,000 - 230,000; Full time

Benefits offered by this job

Medical coverage

Dental coverage

Vision coverage

Maternity leave

Parental leave

Paid time off

401(k) plan

Job summary

Amazon Robotics is seeking an exceptional Applied Scientist to join the Foundation Models and Agentic AI team. You will shape the future of robotics by applying large vision-language-action models, planning, and reinforcement learning to real-world problems.

The role emphasizes model development, data management, experimentation, and collaboration with cross-functional teams to advance robotics research from theory to deployment.

Qualifications

• PhD or Master’s degree required or equivalent
• Experience building machine learning models for business or research applications
• Publications or patents in top-tier venues is a plus

Responsibilities

• Design and implement model architectures, train and fine-tune foundation models on diverse datasets.
• Prepare training data, enforce data governance and build reusable data pipelines.
• Design experiments, validate performance on the simulator and the embodiment, iteratively improve models.
• Write clean, documented code, contribute to training infrastructure and APIs.
• Stay current with foundation models and robotics research; document findings and discoveries.
• Collaborate with senior scientists and engineers; support integration with robotics hardware teams.

Skills

PhD or Master’s level

Machine learning models

Deep learning

Computer vision

Human-robot interaction

Algorithms implementation

Java

C++

Python

Research publications

Education

PhD or Master’s degree

Job description

Amazon Robotics is seeking an exceptional Applied Scientist to join the Foundation Models and Agentic AI team. You will shape the future of robotics by applying large vision-language-action models, planning, and reinforcement learning to real-world problems.

The role emphasizes model development, data management, experimentation, and collaboration with cross-functional teams to advance robotics research from theory to deployment.