Amazon
Job ID: 2851294 | Amazon.com Services LLC
Join the next revolution in robotics at Amazon's Frontier AI & Robotics team. As a Senior Applied Scientist, you'll spearhead the development of breakthrough foundation models that enable robots to perceive, understand, and interact with the world in unprecedented ways. You'll drive technical excellence in areas such as perception, manipulation, science understanding, sim2real transfer, multi-modal foundation models, and multi-task learning, designing novel algorithms that bridge the gap between research and real-world deployment at Amazon scale.
In this role, you'll combine hands-on technical work with scientific leadership, ensuring your team delivers robust solutions for dynamic real-world environments. You'll leverage Amazon's vast computational resources to tackle ambitious problems in areas like very large multi-modal robotic foundation models and efficient, promptable model architectures that can scale across diverse robotic applications.
Key job responsibilities
Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish Guide technical direction for specific research initiatives, ensuring robust performance in production environments 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
A day in the life
Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure Guide fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems Drive technical discussions within your team and with key stakeholders Conduct experiments and prototype new ideas using our massive compute cluster Mentor team members while maintaining significant hands-on contribution to technical solutions
BASIC QUALIFICATIONS
PhD, or Master's degree and 6+ years of applied research experience 3+ years of industry or academic research experience Experience programming in Java, C++, Python or related language Strong publication record at top-tier conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, RSS, CoRL) Strong track record of leading technical projects Experience mentoring junior scientists/engineers Demonstrated expertise in deep learning and model development
PREFERRED QUALIFICATIONS
History of impactful first-author publications at major conferences Experience leading research initiatives in robotics or foundation models Track record of successful production ML deployments Experience with large-scale distributed systems History of technical leadership and team mentorship Experience bridging research with practical engineering implementation
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
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Key job responsibilities
Lead technical initiatives in robotics foundation models, driving breakthrough approaches through hands-on research and development in areas like open-vocabulary panoptic scene understanding, scaling up multi-modal LLMs, sim2real/real2sim techniques, end-to-end vision-language-action models, efficient model inference, video tokenization Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish Guide technical direction for specific research initiatives, ensuring robust performance in production environments 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
A day in the life
Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure Guide fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems Drive technical discussions within your team and with key stakeholders Conduct experiments and prototype new ideas using our massive compute cluster Mentor team members while maintaining significant hands-on contribution to technical solutions
BASIC QUALIFICATIONS
PhD, or Master's degree and 6+ years of applied research experience 3+ years of industry or academic research experience Experience programming in Java, C++, Python or related language Strong publication record at top-tier conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, RSS, CoRL) Strong track record of leading technical projects Experience mentoring junior scientists/engineers Demonstrated expertise in deep learning and model development
PREFERRED QUALIFICATIONS
History of impactful first-author publications at major conferences Experience leading research initiatives in robotics or foundation models Track record of successful production ML deployments Experience with large-scale distributed systems History of technical leadership and team mentorship Experience bridging research with practical engineering implementation
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.
#J-18808-Ljbffr