Principal, Applied Scientist, AWS Applied AI Solutions

Amazon is hiring a Principal, Applied Scientist, AWS Applied AI Solutions in Seattle, United States. It pays $199k-$269k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
The listed pay starts 16% above the typical applied scientist posting on Level.
Tools and skills the posting cites include PyTorch, TensorFlow and computer vision.
Level classifies it as a lead role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

PyTorchTensorFlow

computer-vision

Join us if you're excited about pushing the boundaries of what's possible in physical AI working with world-class scientists and engineers and seeing your innovations deployed at unprecedented scale.

We are seeking an exceptional Principal Applied Scientist to drive technical innovation in visual reasoning foundation models. You will be a technical leader who sets the research direction, architects novel solutions, and delivers breakthrough results that advance the state of the art while solving real-world business problems.

You will lead the efforts of building a next-generation visual reasoning engine powered by frontier Large Video Models (LVMs). Your mission is to build a system that rivals human understanding of the physical world-moving far beyond the static perception of detection and tracking into the realm of deep spatial-temporal reasoning. This is not a passive computer vision tool; it is an agentic collaborator capable of interpreting natural language instructions navigating unstructured environments and executing complex tasks.

You will sit at the high-stakes intersection of LVMs, LLMs, and Agentic AI engineering systems that don't just 'see' but reason and act within the physical world. You will own end-to-end technical solutions from research to production deployment driving innovation through hands-on research prototyping and deployment while delivering production impact.

Key Responsibilities

• Direct the technical vision for next-gen visual reasoning pioneering the use of LVMs to solve high-dimensional spatial-temporal problems
• Design and implement novel deep learning architectures combining a multitude of modalities including image video and geospatial data
• Solve computational challenges to train foundation models at scale taking advantage of latest developments in hardware and deep learning libraries
• Architect scalable solutions that deliver real-time insights across diverse physical environments
• Build agentic AI systems that autonomously execute end-to-end workflows transforming visual data into actionable business intelligence
• Collaborate with multiple science and engineering teams to build adaptations that power use cases across diverse domains
• Publish research at top-tier conferences (CVPR NeurIPS ICML) and establish technical thought leadership in visual reasoning and multi-modal AI
• Mentor scientists and engineers while maintaining significant hands-on contribution to technical solutions
• Influence product roadmaps through deep technical expertise and business acumen

Key job responsibilities
- Direct the technical vision for next-gen visual reasoning, pioneering the use of LVMs to solve high-dimensional spatial-temporal problems
- Design and implement novel deep learning architectures combining a multitude of modalities, including image, video, and geospatial data
- Solve computational challenges to train foundation models at scale, taking advantage of latest developments in hardware and deep learning libraries
- Architect scalable solutions that deliver real-time insights across diverse physical environments
- Build agentic AI systems that autonomously execute end-to-end workflows, transforming visual data into actionable business intelligence
- Collaborate with multiple science and engineering teams to build adaptations that power use cases across diverse domains
- Publish research at top-tier conferences (CVPR, NeurIPS, ICML) and establish technical thought leadership in visual reasoning and multi-modal AI
- Mentor scientists and engineers while maintaining significant hands-on contribution to technical solutions
- Influence product roadmaps through deep technical expertise and business acumen

A day in the life
• Develop and implement novel foundation model architectures working hands-on with data and our extensive training and evaluation infrastructure
• Guide and support fellow scientists in solving complex technical challenges from spatiotemporal reasoning to efficient multi-task learning
• Guide and support fellow engineers in building scalable and reusable infrastructure to support model training evaluation and inference
• Lead focused technical initiatives from conception through deployment ensuring successful integration with production systems
• Drive technical discussions with the team and key stakeholders
• Conduct experiments and prototype new ideas
• Mentor team members while maintaining significant hands-on contribution to technical solutions

About the team
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn't followed a traditional path, or includes alternative experiences, don't let it stop you from applying.

Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.

Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic qualifications

- PhD in computer science, machine learning, engineering, or related fields
- 8+ years of applied research experience
- Have publications on top-tier conferences, such as CVPR, ICCV, ECCV or NeurIPS
- Deep expertise in architecting and training frontier Vision-Language Models (VLMs) or Large Video Models (LVMs), with proven ability to design novel algorithms that advance the state of the art in spatiotemporal understanding
- Experience translating research into production systems at scale
- Excellent programming skills in Python and deep learning frameworks (PyTorch, TensorFlow)

Preferred qualifications

- Deep expertise in World Models, Neural Radiance Fields (NeRFs/Gaussian Splatting), and long-horizon spatiotemporal reasoning
- Demonstrated leadership in building and scaling agentic AI applications in production
- A history of building and scaling world-class teams and mentoring senior ICs to achieve career breakthroughs

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

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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, WA, Seattle - 198,900.00 - 269,000.00 USD annually

How we rate this

Principal, Applied Scientist, AWS Applied AI Solutions at Amazon rates 99 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Principal, Applied Scientist, AWS Applied AI Solutions is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $199k-$269k a year.
The role is based in US, WA, Seattle.
The job was posted on February 3, 2026.
Seniority: lead.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionPyTorchTensorFlow

Also common in applied scientist jobs at this level

C++Java Generative AI NLP Reinforcement learning Spark

Pay

This job starts at: $199k
Typical applied scientist job: $172k

This posting starts 16% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
Walk me through how you've used PyTorch in your day-to-day work.
What are the limits of TensorFlow that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

List these exact terms on your resume: Computer vision, PyTorch, and TensorFlow. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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