Principal Applied Scientist, FAR (Frontier AI & Robotics)

Amazon; Dallas (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

An established industry player is seeking a Principal Applied Scientist to join their pioneering robotics team. In this role, you'll be at the forefront of developing groundbreaking foundation models that empower robots to understand and interact with their environment. You will engage in hands-on research while providing scientific leadership, ensuring that your team delivers innovative solutions for real-world applications. This position offers the chance to work with cutting-edge technology and collaborate with leading experts in the field, making a significant impact in the world of robotics and AI. If you are passionate about pushing the boundaries of technology and want to be part of a transformative journey, this opportunity is for you.

Benefits

Medical Coverage

Dental Coverage

Vision Coverage

Maternity Leave

Parental Leave

Paid Time Off

401(k) Plan

Qualifications

• PhD or Master's with 6+ years in applied research and industry experience.
• Expertise in deep learning, mentoring, and leading technical projects.

Responsibilities

• Lead initiatives in robotics foundation models and novel deep learning architectures.
• Mentor scientists while contributing significantly to technical solutions.

Skills

Deep Learning

Machine Learning

Java

C++

Python

Technical Leadership

Mentoring

Education

PhD

Master's degree

Tools

Compute Infrastructure

Robotics Systems

Job description

Job ID: 2961268 | Amazon.com Services LLC

Join the next revolution in robotics at Amazon's Frontier AI & Robotics team, where you'll work alongside world-renowned AI pioneers to lead key initiatives in robotic intelligence. As a Principal 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 state-of-the-art 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

1. 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.
2. Design and implement novel deep learning architectures that push the boundaries of what robots can understand and accomplish.
3. Guide technical direction for specific research initiatives, ensuring robust performance in production environments.
4. Mentor and support fellow scientists while maintaining strong individual technical contributions.
5. Collaborate with engineering teams to optimize and scale models for real-world applications.
6. Influence technical decisions and implementation strategies within your area of focus.

A day in the life

1. Develop and implement novel foundation model architectures, working hands-on with our extensive compute infrastructure.
2. Guide and support fellow scientists in solving complex technical challenges, from sim2real transfer to efficient multi-task learning.
3. Lead focused technical initiatives from conception through deployment, ensuring successful integration with production systems.
4. Drive technical discussions within your team and with key stakeholders.
5. Conduct experiments and prototype new ideas using our massive compute cluster.
6. Mentor team members while maintaining significant hands-on contribution to technical solutions.

Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include:

1. Medical, Dental, and Vision Coverage
2. Maternity and Parental Leave Options
3. Paid Time Off (PTO)
4. 401(k) Plan

If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!

BASIC QUALIFICATIONS

1. PhD, or Master's degree and 6+ years of applied research experience.
2. 5+ years of industry or academic research experience.
3. Experience programming in Java, C++, Python or related language.
4. 5+ years of building machine learning models or developing algorithms for business application experience.
5. Experience in patents or publication at top-tier conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, RSS, CoRL).
6. Extensive track record of leading technical projects.
7. Experience mentoring junior scientists / engineers.
8. Demonstrated expertise in deep learning and model development.

PREFERRED QUALIFICATIONS

1. Experience as first-author publications at major conferences.
2. Experience leading research initiatives in robotics or foundation models.
3. Track record of successful production ML deployments.
4. Experience with large-scale distributed systems.
5. Experience in technical leadership and team mentorship.
6. Experience bridging research with practical engineering implementation.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.