Principal Applied Scientist, FAIM (Full Funnel Agentic Intelligence and Models)

Amazon is hiring a Principal Applied Scientist, FAIM (Full Funnel Agentic Intelligence and Models) in New York, United States. It pays $229k-$309k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

Level rates this applied scientist role Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts 33% higher than the typical applied scientist posting on Level.
The posting mentions Rl Gym, LLMs and machine learning among its tools and skills.
Amazon has 21,000+ other open roles on Level.
Posted within the past week.

AI in this role

Lead the science vision and invent foundational multimodal models, LLM-driven agents, and RL Gym training processes for advertising workflows.

rl-gymllms

machine-learningoptimizationreinforcement-learningmultimodal-modelsapplied-science

The FAIM (Full Funnel Agentic Intelligence and Models) builds the agentic AI systems behind next-generation advertising. The team develops multimodal foundation models and LLM-driven agents that power shopper understanding, audience-aware creative generation, and agentic advertising workflows.

As a Principal Applied Scientist for the FAIM team, you will invent the models that help advertisers achieve desired outcomes. Today's state of the art models can setup ad campaigns to a specification, but do not understand advertising strategy well enough to help with abstract goals that real advertisers ask about like "how can I make more money."

This is a rare charter to build foundational optimization science where little exists today, spanning campaign recommendation, cross-product budget allocation, incrementality measurement, and long-term-sales modeling. You will set technical direction for a growing team, partner with engineering and product to take models from research to production at Amazon scale, and directly move advertiser ROAS and new-to-brand growth.

In this role you will
- Own the science vision for training models in our RL Gym from end-to-end
- Invent models for joint budget allocation, incrementality, and long-term value
- Take innovations from prototype to production serving live advertiser campaigns
- Raise the technical bar across scientists and engineers

Key job responsibilities
- Define the long-term scientific vision for our RL Gym based training process focusing on campaign optimization and other advertising workflows
- Translating ambiguous advertiser needs and competing objectives into a concrete science roadmap.
- Invent, prototype, and productionize machine learning and optimization solutions for joint budget allocation across sponsored ad products, spanning the shopper journey from awareness to purchase.
- Develop rigorous approaches to incrementality measurement and long-term-sales modeling that ground optimization in true advertiser value.
- Design and lead large-scale experiments and analyses to validate hypotheses and guide product direction.
- Partner closely with engineering and product to define technical contracts, data schemas, and serving systems that carry models into production.
- Raise the technical bar across science and engineering through mentorship, design reviews, and hands-on collaboration.
- Grow scientific talent and publish impactful research internally and at top-tier venues.

Basic qualifications

- PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
- 5+ years of hands-on experience in predictive modeling and analysis
- Experience distilling informal customer requirements into problem definitions while dealing with ambiguity and competing objectives
- Experience programming in Java, C++, Python, or related language
- Experience leading experienced scientists, as well as a record of developing junior members from academia or industry into a career track in a business environment

Preferred qualifications

- 10+ years of relevant experience in industry or academia
- Knowledge of problem solving, algorithm design, and complexity analysis
- Experience creating novel algorithms and advancing the state of the art
- Peer-reviewed scientific contributions in premier journals and conferences

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

Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

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, CA, Palo Alto - 228,700.00 - 309,400.00 USD annually
USA, NY, New York - 218,800.00 - 295,900.00 USD annually
USA, WA, SEATTLE - 198,900.00 - 269,000.00 USD annually

How we rate this

Principal Applied Scientist, FAIM (Full Funnel Agentic Intelligence and Models) at Amazon rates 100 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, FAIM (Full Funnel Agentic Intelligence and Models) is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $229k-$309k a year.
The role is based in US, NY, New York.
The job was posted on October 20, 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

Machine learningOptimizationReinforcement learningMultimodal ModelsApplied ScienceRl GymLLMs

Also common in applied scientist jobs at this level

Deep learning Generative AI NLP TensorFlow Spark Computer vision

Pay

This job starts at: $229k
Typical applied scientist job: $172k

This posting starts 33% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where optimization was part of your work. What did you do?
Tell me about a project where reinforcement learning was part of your work. What did you do?
Tell me about a project where multimodal models was part of your work. What did you do?
Tell me about a project where applied science was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Machine learning, Optimization, Reinforcement learning, Multimodal Models, and Applied Science. 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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