AmazonPrincipal Applied Scientist, Mission AI Lab, AWS Region Services
Amazon is hiring a Principal Applied Scientist, Mission AI Lab, AWS Region Services in Arlington, United States. It pays $199k-$269k a year and Level rates it ; you can apply on Amazon.
Level's read on this job
- Builds AI ●●●● is how Level rates this applied scientist role: the job is building AI systems.
- Pay on this posting starts 19% higher than the typical applied scientist posting on Level.
- The posting mentions fine tuning among its tools and skills.
- Amazon has 22,000+ other open roles on Level.
- Posted in the last few days.
AI in this role
Much of this has no established playbook. There is no benchmark to tell you a model is ready, so you will invent both the method that gets it there and the measure that proves it. The lab is purpose-built for this work and you join at the start, helping shape its technical direction and building the methods and evaluations that carry forward into everything it does next.
This is a hands-on role. You will research the state of the art science, make the calls on how models are trained and evaluated, write code and work alongside the engineers who run the infrastructure, and partner directly with the analysts and operators who depend on the work. You will also explain what the models can and cannot yet do, in plain terms, to the people whose decisions rely on them.
The candidate selected must obtain and maintain a security clearance at the TS/SCI with polygraph level. Upon start, the selected candidate will be sponsored for a commensurate clearance for each government agency for which they perform AWS work.
Key job responsibilities
• Own the end-to-end adaptation of frontier models for complex reasoning tasks, from supervised fine-tuning and post-training through reinforcement learning, delivered as production systems people can rely on in the field
• Define what "good" means for each task, building the evaluation sets, test harnesses, and metrics that measure model quality where no public benchmark exists
• Build and own the data pipelines that turn raw operational data into high-signal training and evaluation sets, including curation, quality scoring, provenance tracking, and strict leakage and contamination controls
• Judge when a problem needs a genuinely new method versus an extension of an existing one, and make the call with evidence
• Choose the training and adaptation methods, including parameter-efficient techniques, that turn serious dedicated compute into the largest gains in capability
• Extend adapted models into new priority domains, owning transferability, generalization, and calibration under real-world distribution shift
• Run data-preparation and human-in-the-loop feedback loops with the analysts who know the problems best, turning their expertise into better data and sharper evaluations
• Package methods and evaluations so they can be reused as the lab's work grows, and shared with Amazon's model teams
• Represent the lab's science in technical reviews and to program and technical leaders, surfacing what the models can do and where the risks are
• Help set the technical bar for the lab, and mentor scientists as the team grows
A day in the life
You start the morning reviewing an overnight fine-tuning run against an evaluation suite you built, checking whether the adapted model beats the base on the metrics that matter most. Mid-morning, you work with the engineers who run the infrastructure to get a large training run moving and squeeze the most capability out of it. After lunch, you sit with domain analysts to turn their feedback into a cleaner, better-labeled evaluation set for a change-detection task, then decide whether the next gain calls for a new method or an extension of one you already have. You close the day documenting that method and evaluation so the rest of the lab can build on it, and writing a short, plain-language readout of what the model can and cannot yet do for the people who depend on it.
About the team
The Mission AI Model Lab is the science team behind AWS's Mission AI program. We take existing models and make them useful for problems that matter to national security, working on dedicated AI infrastructure built for exactly that. This lab is purpose-built and these are among its first scientists, so the people who join now help shape how it works and what it builds. We sit where frontier-model research meets national security delivery, and we value invention on genuinely new problems, evaluation we can defend, and plain talk with the people who rely on what we build.
Basic qualifications
- 5+ years of hands-on work in predictive modeling and analysis experience
- PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
- Experience working in predictive modeling and analysis
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
- Experience programming in Java, C++, Python or related language
- Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment
Preferred qualifications
- 10+ years of relevant work in industry or academia experience
- Knowledge of problem solving, algorithm design and complexity analysis
- Experience creating novel algorithms and advancing the state of the art
- Current, active TS/SCI US Government Security Clearance
- Experience at a frontier AI lab, national lab, defense AI company, or government research program
- Parameter-efficient fine-tuning (LoRA-style methods) and efficient training within a fixed compute budget
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, VA, Arlington - 198,900.00 - 269,000.00 USD annually
How we rate this
Principal Applied Scientist, Mission AI Lab, AWS Region Services at Amazon rates 93 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.
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.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $199k
- Typical applied scientist job
- $167k
This posting starts 19% above the typical applied scientist job. See applied scientist jobs
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- 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: Fine-tuning. 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.
Want an expert to read your CV for this job?
Free. Send your CV and the role you want next. We reply by email within 2 to 4 business days.
Get new applied scientist jobs (Builds AI ●●●●) by email
One email a week with the new applied scientist jobs (Builds AI ●●●●), each rated for how much AI is in the work. No recruiter spam, unsubscribe in one click.
Free. One email a week. Unsubscribe in one click.
Similar roles
Research roles that build AI, at other companies.
What kind of AI work fits you?
Answer 12 practical questions in about three minutes. Get a simple profile, the work it points to, and live roles to explore next.
Find my next step