Applied Scientist, Robotics Foundations & AI

Amazon; Sunnyvale (CA); On-site; USD 172,000 - 222,000; Full time

Job summary

Amazon Robotics is seeking an exceptional Applied Scientist to join our Foundation Models and Agentic AI team in Sunnyvale, CA. You will help shape the future of robotics by advancing large vision-language-action models, planning, and reinforcement learning, applying them to real-world automation challenges.

You will design architectures, train foundation models, and collaborate with engineers and researchers to deploy robust AI systems across robotic platforms.

Qualifications

• PhD or Master's degree with 4+ years of ML model development.
• 2+ years in deep learning, computer vision, HRI or related areas.
• Experience with patents or publications in top conferences or journals.
• Proficiency in Java, C++, or Python.

Responsibilities

• Model Development and Training: Design and implement model architectures, train and fine-tune foundation models with diverse data, and improve performance via iterative experiments.
• Data Management: Prepare data, ensure governance, provenance, quality checks, and reusable pipelines.
• Experimentation and Validation: Design/execute experiments on simulator and embodiment, validate performance, establish baselines, improve models.
• Code Development: Write clean, maintainable, documented code; contribute to training infra, tools for evaluation, and APIs.
• Research: Stay current with foundation models and robotics; do literature reviews and document findings.
• Collaboration: Work with senior scientists/engineers, support integration with robotics teams, document best practices.

Skills

PhD or MSc

4+ yrs ML/Algorithms

Deep Learning

Computer Vision

Java/C++/Python

Data Structures

Education

Master's or PhD

Tools

Python

Java

C++

Job description

Amazon Robotics is seeking an exceptional Applied Scientist to join our Foundation Models and Agentic AI team in Sunnyvale, CA. You will help shape the future of robotics by advancing large vision-language-action models, planning, and reinforcement learning, applying them to real-world automation challenges.

You will design architectures, train foundation models, and collaborate with engineers and researchers to deploy robust AI systems across robotic platforms.