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Sr. Applied Scientist, APM Video Science

Amazon is hiring a Sr. Applied Scientist, APM Video Science in New York, United States. It pays $184k-$249k 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 9% higher than the typical applied scientist posting on Level.
  • The posting mentions Bedrock, TensorFlow and scikit-learn among its tools and skills.
  • Amazon has 20,000+ other open roles on Level.
  • Posted in the last few days.

AI in this role

BedrockTensorFlowscikit-learn
computer-vision
Twitch is looking for an Applied Scientist to lead computer vision and video manipulation work within Amazon Publisher Monetization (APM). You will apply large language models (LLMs), vision-language models (VLMs), and traditional computer vision techniques to build products that directly improve how millions of Twitch creators produce content and how viewers engage with it. This is a high-visibility project backed by senior leadership, and you will have the autonomy to evaluate both first-party and third-party solutions to deliver the highest quality results quickly. If you thrive in a fast-paced, startup-like environment where your scientific decisions shape the product roadmap, we want to hear from you.


Key job responsibilities
Design and deploy computer vision and video manipulation models using LLMs, VLMs, and traditional techniques, taking solutions from research prototype to production.
Partner with senior Product and Twitch leadership to translate customer needs into well-defined scientific problems and deliver end-to-end solutions.
Evaluate and integrate generative AI capabilities across Amazon Bedrock and third-party platforms, selecting the approach that maximizes product quality.
Drive the team's scientific agenda by proposing new initiatives, authoring technical documents, and contributing to external publications.
Mentor fellow scientists and engineers through code reviews, design guidance, and technical assessments that raise the overall quality bar.

A day in the life
You will split your time roughly evenly between independent research and collaborative sessions. Mornings often start with focused solo work — benchmarking a new VLM, writing model code, or analyzing experiment results. Midday you join working sessions with Product and Twitch leadership to align on requirements or review progress. Afternoons shift between pairing with engineers on production integration and mentoring teammates on evaluation methodology. Weekly science reviews and bi-weekly roadmap syncs keep the team aligned without over-scheduling your calendar.

About the team
The APM science team supports all of Amazon's Publisher Monetization efforts, building the models and systems behind Twitch's creator tools and ad experiences. The team includes applied scientists, software engineers, and product managers who collaborate daily to move ideas from whiteboard to production. We operate with a startup mentality — moving fast, wearing multiple hats, and iterating closely with Twitch and Product partners. We are accelerating investment in computer vision and generative AI, and this role will be central to that expansion.

Basic qualifications

- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language

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, NY, New York - 183,800.00 - 248,700.00 USD annually

How we rate this

Sr. Applied Scientist, APM Video Science at Amazon rates 89 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.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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

Computer visionBedrockTensorFlowscikit-learn

Also common in applied scientist jobs at this level

Pay

This job starts at
$184k
Typical applied scientist job
$169k

This posting starts 9% above the typical applied scientist job. See applied scientist jobs

Questions you could be asked

  1. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. Walk me through how you've used Bedrock in your day-to-day work.
  3. What are the limits of TensorFlow that you've run into, and how did you work around them?
  4. What's a project where you used scikit-learn hands-on?
  5. How would you decide a model or AI system is ready to ship?

Adapt your resume

  • List these exact terms on your resume: Computer vision, Bedrock, 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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