In this role, you will integrate hands-on technical expertise with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. While staying updated with the latest advancements in robotics research, you will leverage your experience and expertise to guide the team towards the most promising direction. Collaborating with a talented group of software engineers and scientists, you will bring your ideas to fruition. Deploying robots in home environments requires you to anticipate challenges not encountered in structured settings like warehouses. Additionally, consumer-grade sensors and actuators necessitate working around their limitations, requiring out-of-the-box innovative ideas. As such, you are someone who truly enjoys thinking about problems using first principles at a holistic and systems level to address the aforementioned challenges.
Key job responsibilities
- Lead technical initiatives in areas such as robotics foundation models, reinforcement learning and manipulation - - Design experiments to identify the limitations of current state-of-the-art models and developing new models or techniques that can surpass these models
- Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish
- Mentor fellow scientists while maintaining strong individual technical contributions
- Collaborate with engineering teams to optimize and scale models for real-world applications
- Influence technical decisions and implementation strategies within your area of focus
- Experienced in communicating complex technical work to a non-technical audience
- The ability to work with minimal guidance, be proactive and to handle ambiguity and the challenge of quickly evolving goals
A day in the life
- Train ML models for deployment in simulation and real-world robots, identify and document their limitations post-deployment
- Drive technical discussions within your team and with key stakeholders to develop innovative solutions to address identified limitations
- Guide fellow scientists in solving complex technical challenges, from sim2real transfer to training RL policies
- Mentor team members while maintaining significant hands-on contribution to technical solutions
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 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
PREFERRED QUALIFICATIONS
- Hand-on experience of deploying Deep Learning models on robots
- Experience in developing Vision Language Action (VLA) models and/or Reinforcement learning for robot manipulation
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Sunnyvale - 192,200.00 - 260,000.00 USD annually
USA, WA, Bellevue - 167,100.00 - 226,100.00 USD annually
