AmazonSenior Applied Scientist, Brand Protection Machine Learning
Amazon is hiring a Senior Applied Scientist, Brand Protection Machine Learning in Seattle, United States. It pays $167k-$226k 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 close to the typical applied scientist posting on Level.
- Tools and skills the posting cites include TensorFlow, scikit-learn and computer vision.
- Level lists 20,000+ other open roles at Amazon.
- The role was posted in the last few days.
AI in this role
As a Senior Applied Scientist on this team, you will design and execute the science strategy for complex, ambiguous problems. You will develop multi-modal and LLM-based approaches that extract key information from product detail pages, assist human decision-making, and ultimately enable autonomous decisions at scale. You will partner closely with junior scientists, engineers, and product teams to take solutions from research through production, owning the end-to-end lifecycle. Your work will directly shape how Amazon protects the integrity of its marketplace.
Key job responsibilities
Design and execute the science strategy for complex brand-protection problems, selecting the right combination of computer vision, multi-modality, and LLM techniques to deliver production-ready solutions at scale.
Collaborate with product managers, engineering partners, and fellow scientists to translate business challenges into well-defined machine learning experiments, iterating from prototype to launch.
Analyze large volumes of structured and unstructured data to surface insights, inform model design, and continuously improve detection accuracy.
Mentor junior scientists through code reviews, experiment design guidance, and technical discussions, raising the overall scientific rigor of the team.
Publish research findings in top-tier journals and conferences, contributing to the broader scientific community while advancing Amazon's brand-protection capabilities.
A day in the life
You will split your time between hands-on research and collaboration. A typical stretch includes designing and running experiments on multi-modal models, reviewing results with product and engineering partners, and brainstorming next steps in working sessions. You operate proactively, driving your own roadmap rather than reacting to incoming requests, while regularly syncing with stakeholders to keep your science strategy aligned with business priorities. There are no direct reports; your influence comes through technical leadership and mentorship.
About the team
The Brand Protection applied science team is a centralized group of approximately 20 scientists with PhDs from a wide range of quantitative backgrounds. We sit within Selling Partner Services and work closely with product, engineering, and fellow science teams to build AI systems that safeguard brand owners and customers across Amazon's marketplace. You will have the opportunity to work with generative AI and the latest multi-modality models, and your innovations can lead to publications in top journals — making this a place where applied research and customer impact go hand in hand.
Basic qualifications
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field, or Master's degree and 4+ years of building machine learning models or developing algorithms for business application experience
- 3+ years of building machine learning models for business application experience
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)
- Experience with neural deep learning methods and machine learning
- Experience programming in Java, C++, Python or related language
- PhD, or Master's degree and 6+ years of applied research experience
- 5+ years of applied research experience
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.
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 - 167,100.00 - 226,100.00 USD annually
How we rate this
Senior Applied Scientist, Brand Protection Machine Learning at Amazon rates 97 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
Also common in applied scientist jobs at this level
Pay
- This job starts at
- $167k
- Typical applied scientist job
- $172k
This posting starts close to 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.
- What NLP problem have you worked on, and how did you measure whether it actually worked?
- What have you built with speech recognition or text-to-speech, and where did it break?
- 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: Computer vision, NLP, Speech, 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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