AmazonApplied Scientist II, Prime Video Personalization and Discovery Science, Prime Video - Personalization and Discovery Science
Amazon is hiring an Applied Scientist II, Prime Video Personalization and Discovery Science, Prime Video - Personalization and Discovery Science in Sunnyvale, United States. It pays $172k-$222k 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 in line with the typical applied scientist posting on Level.
- The posting mentions Deep learning, Python and foundation models among its tools and skills.
- Level classes it as a senior role.
- Amazon has 20,000+ other open roles on Level.
AI in this role
Develop foundation models and deep learning techniques for content understanding and customer behavior prediction in Prime Video.
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!
Key job responsibilities
Develop foundation models for content understanding using state-of-the-art deep learning and multimodal learning techniques to analyze video and text
Build time sequence foundation models to understand and predict customer behavior patterns and viewing trajectories
Work closely with engineers and product managers to design, implement and launch solutions end-to-end across various Prime Video experiences
Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses
Effectively communicate technical and non-technical ideas with teammates and stakeholders
Stay up-to-date with advancements and the latest modeling techniques in foundation models, multimodal learning, and time series analysis
Publish your research findings in top conferences and journals
A day in the life
We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative & customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences.
About the team
Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.
Basic qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred qualifications
- Experience using Unix/Linux
- Experience in professional software development
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 - 171,600.00 - 222,200.00 USD annually
USA, NY, New York - 172,400.00 - 223,400.00 USD annually
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually
How we rate this
Applied Scientist II, Prime Video Personalization and Discovery Science, Prime Video - Personalization and Discovery Science at Amazon rates 95 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
- $172k
- Typical applied scientist job
- $167k
This posting starts close to the typical applied scientist job. See applied scientist jobs
Questions you could be asked
- Tell me about a project where foundation models was part of your work. What did you do?
- Tell me about a project where multimodal learning was part of your work. What did you do?
- Tell me about a project where time series analysis was part of your work. What did you do?
- Tell me about a project where machine learning was part of your work. What did you do?
- Walk me through how you've used Deep learning in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Foundation Models, Multimodal Learning, Time Series Analysis, Machine learning, and Deep learning. 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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