AmazonPosted 3mo ago

Senior Applied Scientist, Linear Personalization Experience Team (LPEX)

Senior Applied Scientist, Linear Personalization Experience Team (LPEX) at Amazon scores 92 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Seattleseniorfull-time$192k-$260k

AI in this role

tensorflowscikit-learnsagemaker

ai-research

Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports – including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads.

Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.

As a Prime Video technologist, you’ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You’ll get to work on projects that are fast-paced, challenging, and varied. You’ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people.

We’ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you!

Prime Video is disrupting traditional media with an ever-increasing selection of movies, TV shows, Emmy Award-winning original content, add-on subscriptions, and live events like Thursday Night Football. Within this expanding ecosystem, Linear TV with its 24/7 scheduled broadcast-style programming has emerged as one of our fastest-growing segments, with viewership hours increasing significantly year over year. This growth demonstrates that even in the streaming era, customers deeply value the lean-back, curated experience that Linear TV provides.

Key job responsibilities
As an Applied Scientist on LPEX, you will be a technical owner and science leader across the following areas:
* Define and drive the science strategy and multi-year roadmap for Linear TV personalization, translating research advances into measurable business and customer experience outcomes.
* Design, develop, and deploy machine learning models for content recommendation, viewer engagement optimization, and real-time personalization at the scale of hundreds of millions of Prime Video customers.
* Own the complete ML lifecycle: problem formulation, data analysis, feature engineering, model development, offline and online evaluation, and reliable production deployment.
* Build and continuously optimize recommendation systems with strict real-time latency requirements, ensuring that personalization decisions are delivered at speed and scale.
* Design and execute rigorous A/B and multivariate experiments to measure recommendation quality, understand causal drivers of engagement, and iterate rapidly toward customer impact.
* Partner with software engineering teams to productionize ML models, defining requirements for serving infrastructure, data pipelines, and model monitoring and observability.
* Collaborate with product managers and cross-functional stakeholders to translate ambiguous business problems into well-scoped, tractable science solutions.
* Publish research findings and contribute to the broader scientific community through papers, patents, and internal knowledge-sharing forums.
* Mentor scientists and engineers on the team, setting a high bar for scientific rigor, experimental discipline, and ML engineering best practices.

A day in the life
We are looking for an Applied Scientist who will define and drive the science strategy for personalization and recommendations on Linear TV. You will own the end-to-end machine learning lifecycle from problem formulation and research through experimentation and production deployment, building systems that help millions of customers discover the right content at the right time. It's Day 1 for personalizing the linear TV experience on Prime Video, and you will be at the forefront of this innovation.

About the team
The Linear Personalization Experience (LPEX) team is building next-generation, AI-powered personalization and recommendation systems to enhance this natural engagement and deliver a best-in-class Linear TV experience for Prime Video customers worldwide.

The LPEX team's vision is to surface the breadth and depth of Prime Video's linear selection at exactly the right moment for each customer curating the most relevant programming, tailored to individual tastes, purchase behaviors, schedules, and viewing habits, while simultaneously elevating awareness of our extensive live and linear catalog.

Our mission is to anticipate and exceed viewers' expectations, fostering deeper connections with the content they love. We adapt to viewers' preferences and propensities for both live and on-demand viewing, enriching the overall entertainment journey. The team operates at the intersection of machine learning research, large-scale distributed systems, and consumer product strategy, partnering closely with product management, engineering, and business development.

Basic qualifications

- PhD, or Master's degree and 6+ years of applied research experience
- 5+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning

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 in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning
- Experience with AWS services including S3, Redshift, Sagemaker, EMR, Kinesis, Lambda, and EC2
- Experience with statistical methods (e.g., A/B Testing, Regression)
- Experience in written and verbal communication skills to communicate with technical and non-technical audiences, including senior leadership

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, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

AI ResearchTensorFlowscikit-learnSagemaker

Questions you could be asked

Tell me about a research question you investigated. What did you find?
Walk me through how you've used TensorFlow in your day-to-day work.
What are the limits of scikit-learn that you've run into, and how did you work around them?
What's a project where you used Sagemaker hands-on?
How would you decide a model or AI system is ready to ship?

Adapt your resume

List these exact terms on your resume: AI Research, TensorFlow, scikit-learn, and Sagemaker. 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 your resume actually rewritten for this job?

The free preview above is everything we have today. A full resume rewrite is not live yet and has no price set. Join the waitlist and we will email you if we open it.