Senior Applied Scientist — Robotics & Real-World AI

Amazon; Sunnyvale (CA); On-site; USD 192,000 - 260,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Fauna Robotics, an Amazon company, seeks an Applied Scientist to advance perception, manipulation, sim2real transfer, reinforcement learning and multi-task learning for home robotics. You will integrate hands-on expertise with scientific leadership to deliver robust solutions for dynamic real-world environments.

Collaborating with software engineers and scientists, you will guide research-to-deployment efforts, ensuring scalable, safe and user-friendly robotic systems in homes.

Qualifications

• 3+ years building machine learning models for business or applied robotics
• PhD or Master’s with 6+ years of applied research experience
• Experience with neural deep learning methods and machine learning
• Strong publication record at major Robotics/ CV conferences (e.g., RSS, CoRL, ICRA, IROS, NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV)
• Experience programming in Python, C++, or related language

Responsibilities

• Lead technical initiatives in robotics foundation models, RL and manipulation; design experiments to beat current state-of-the-art models
• Design and implement novel deep learning architectures for robot understanding and capabilities
• Mentor fellow scientists while contributing hands-on work
• Collaborate with engineering teams to optimize and scale models for real-world applications
• Influence technical decisions and implementation strategies within your focus area
• Communicate complex technical work to non-technical audiences
• Work with minimal guidance, be proactive, and handle ambiguity in evolving goals

Skills

Machine learning in robotics

Python

C++

Research leadership

Education

PhD or MS + 6+ years applied research

Tools

Python

C++

Job description

Fauna Robotics, an Amazon company, seeks an Applied Scientist to advance perception, manipulation, sim2real transfer, reinforcement learning and multi-task learning for home robotics. You will integrate hands-on expertise with scientific leadership to deliver robust solutions for dynamic real-world environments.

Collaborating with software engineers and scientists, you will guide research-to-deployment efforts, ensuring scalable, safe and user-friendly robotic systems in homes.