Sr. Applied Scientist, Sales AI

Amazon is hiring a Sr. Applied Scientist, Sales AI in Sunnyvale, United States. It pays $192k-$260k 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 15% higher than the typical applied scientist posting on Level.
The posting mentions TensorFlow, scikit-learn and fine tuning among its tools and skills.
Amazon has 20,000+ other open roles on Level.
Posted in the last few days.

AI in this role

TensorFlowscikit-learn

fine-tuningcomputer-visionnlp

Love using AI to solve big, messy problems that actually move a business? Join Sales AI as an Applied Scientist and own the science behind how Amazon Ads helps every advertiser grow, from understanding where each brand is on its growth journey to building the GenAI agents account teams use every day.

Advertising is one of the fastest growing parts of our business, and science sits at the heart of how we help brands succeed. Our scientists work on two connected problems. The first is figuring out, for each brand, the smartest next step it can take to grow, and turning that into a clear, personalized recommendation. The second is building LLM-powered assistants and agents that put that intelligence into the hands of the people who work with those brands, accurately and at scale. If you want real ownership, hard problems, and models that ship, we'd love to talk.

Key job responsibilities
You'll own production science systems that account teams rely on every day. For example, you might build the recommendation engine that maps where each advertiser is in their growth journey and what their best next step is, or improve the accuracy of the LLM-powered assistants and agents that account teams use to prepare for and run customer conversations. Day to day that means:

- Turn ambiguous business problems into well-defined science problems, and choose the right approach to solve them
- Build, ship, and continuously improve models in production, and own their quality once they launch
- Measure whether our models really move the business, through A/B tests, causal analysis, and offline evaluation
- Partner with engineers and product managers to take ideas from early research into production
- Set the technical direction for your area, raise the scientific bar, and mentor other scientists
- Explain complex methods and trade-offs clearly to engineers, product partners, and sales leaders

A day in the life
No two days look the same. You might start by testing a new modeling approach, then review evaluation results with engineers to decide whether a model is ready to launch. Later you could meet with product partners to agree on what to build next, or dig into data to understand why a recommendation isn't landing. Your customers are the account teams who work directly with brands, and the brands themselves, who rely on your work to decide where to invest and how to grow.

About the team
Sales AI is a central science and data engineering organization within Amazon Advertising Sales. Our mission is to power selling motions and account team workflows with state-of-the-art AI and ML services. We build advertiser insights, recommendations, and generative AI-powered applications woven throughout account team workflows. We care about a high scientific bar, real business impact, and taking ideas all the way into production. Most of all, we like working with curious people who want to drive real, lasting impact for our customers.

Basic qualifications

- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience in building machine learning models for business application
- Experience with one of the following areas: machine learning technologies, Reinforcement Learning, Deep Learning, Computer Vision, Natural Language Processing (NLP) or related applications

Preferred qualifications

- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- Experience with neural deep learning methods and machine learning
- Applied research experience in Reinforcement Learning (RLHF, policy gradient methods), Large Language Models (fine-tuning, guardrails, distributed training) and/or Natural Language Processing

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, Sunnyvale - 192,200.00 - 260,000.00 USD annually
USA, NY, New York - 183,800.00 - 248,700.00 USD annually
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually

How we rate this

Sr. Applied Scientist, Sales AI at Amazon rates 91 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

Sr. Applied Scientist, Sales AI is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $192k-$260k a year.
The role is based in US, CA, Sunnyvale.
The job was posted on November 13, 2026.
Seniority: senior.
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

Fine-tuningComputer visionNLPTensorFlowscikit-learn

Also common in applied scientist jobs at this level

AWS PyTorch SQL AI agents RAG Hugging Face

Pay

This job starts at: $192k
Typical applied scientist job: $167k

This posting starts 15% 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?
Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
What's a project where you used TensorFlow hands-on?
Walk me through how you've used scikit-learn in your day-to-day work.

Adapt your resume

List these exact terms on your resume: Fine-tuning, Computer vision, NLP, TensorFlow, and scikit-learn. 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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