Applied AI Robotics Research Intern

Amazon Science; San Francisco (CA); On-site; USD 127,000 - 172,000; Full time

Benefits offered by this job

Mentorship from industry luminaries

State-of-the-art computing resources

Job summary

Amazon Science in San Francisco, CA is seeking an Applied Science Intern to push AI/robotics boundaries under world‑class researchers. You will explore deep learning, reinforcement learning, computer vision, and motion planning while leveraging cutting‑edge hardware and mentorship from industry leaders.

You will contribute to scalable algorithms and analysis on real robotic problems, collaborating with teams to deliver impactful insights and solutions in a fast‑paced research environment.

Qualifications

• Enrolled in a Bachelor’s degree or above
• Must be eligible for full‑time (40 hours per week) internship for the entire duration
• Relocation to the internship base may be required
• Experience with Python; C++ or JAX as applicable
• Publications, thesis work, or equivalent demonstrated depth in a research area

Responsibilities

• Develop novel, scalable algorithms and modeling techniques at the intersection of LLMs and robotics
• Tackle challenging research problems on production-scale data focused on perception, manipulation, and control
• Collaborate with cross-functional teams to communicate findings and advance AI robotics research
• Demonstrate independence, adaptability, and effective communication with diverse stakeholders

Skills

Machine learning

Deep learning

Robotics

Publication record

Python

PyTorch

JAX

Problem solving

Education

Bachelor's degree or higher

Tools

MuJoCo

Isaac Sim

C++

Job description

Amazon Science in San Francisco, CA is seeking an Applied Science Intern to push AI/robotics boundaries under world‑class researchers. You will explore deep learning, reinforcement learning, computer vision, and motion planning while leveraging cutting‑edge hardware and mentorship from industry leaders.

You will contribute to scalable algorithms and analysis on real robotic problems, collaborating with teams to deliver impactful insights and solutions in a fast‑paced research environment.