Applied Scientist, Prime Video - Generative AI

$171K - $222K Sunnyvale, CA, US Mid Level Research Scientist

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Skills & Technologies

PythonPytorchTensorflowTransformers

About This Role

AI job market dashboard showing open roles by category

DESCRIPTION

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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 subscriptions such as Apple TV\+, HBO Max, Peacock, 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 team member, 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

As an Applied Scientist at Prime Video, you will have end\-to\-end ownership of the product, related research and experimentation, applying advanced machine learning techniques in computer vision (CV), Generative AI, multimedia understanding and so on.

You’ll work on diverse projects that enhance Prime Video’s content localization, image/video understanding, and content personalization, driving impactful innovations for our global audience. Other responsibilities include:

  • Research and develop generative models for controllable synthesis across images, video, vector graphics, and multimedia
  • Innovate in advanced diffusion and flow\-based methods (e.g., inverse flow matching, parameter efficient training, guided sampling, test\-time adaptation) to improve efficiency, controllability, and scalability.
  • Advance visual grounding, depth and 3D estimation, segmentation, and matting for integration into pre\-visualization, compositing, VFX, and post\-production pipelines.
  • Design multimodal GenAI workflows including visual\-language model tooling, structured prompt orchestration, agentic pipelines.

A day in the life

Prime Video is pioneering the use of Generative AI to empower the next generation of creatives. Our mission is to make world\-class media creation accessible, scalable, and efficient.

We are seeking an Applied Scientist to advance the state of the art in Generative AI and to deliver these innovations as production\-ready systems at Amazon scale. Your work will give creators unprecedented freedom and control while driving new efficiencies across Prime Video’s global content and marketing pipelines. This is a newly formed team within Prime Video Science!BASIC QUALIFICATIONS

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  • 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
  • 3\+ years of building models for business application experience
  • Ph.D. in computer science, engineering, mathematics or equivalent, or experience with Machine and Deep Learning toolkits such as MXNet, TensorFlow, Caffe and PyTorch
  • Experience in generative models (diffusion, flow, transformers)
  • Hands\-on experience with image/video synthesis and editing techniques

PREFERRED QUALIFICATIONS

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  • Publications in top\-tier AI/ML/Graphics Conferences (CVPR, ICCV/ECCV, SIGGRAPH, NeurIPS, ICLR)
  • Experience with controllable generation methods, including emerging approaches (familiarity with LoRA/ControlNet, parameter\-efficient tuning, or test\-time training a plus)
  • Expertise in one or more of: harmonization, relighting, style transfer, lip\-sync, segmentation, matting, depth estimation, 3D camera/scene modeling.

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

Salary Context

This $171K-$222K range is above the median for Research Scientist roles in our dataset (median: $196K across 93 roles with salary data).

Role Details

Company Amazon.com
Title Applied Scientist, Prime Video - Generative AI
Location Sunnyvale, CA, US
Category Research Scientist
Experience Mid Level
Salary $171K - $222K
Remote No

About This Role

Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.

The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.

Across the 3,824 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Amazon.com, this role fits into their broader AI and engineering organization.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

What the Work Looks Like

A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

Skills Required

Python (51% of roles) Pytorch (15% of roles) Tensorflow (13% of roles) Transformers (3% of roles)

PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.

Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.

Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

Compensation Benchmarks

Research Scientist roles pay a median of $223,400 based on 223 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($196K) sits 12% below the category median. Disclosed range: $171K to $222K.

Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.

Amazon.com AI Hiring

Amazon.com has 98 open AI roles right now. They're hiring across AI/ML Engineer, Research Scientist, AI Product Manager, Data Scientist. Positions span New York, NY, US, Seattle, WA, US, Sunnyvale, CA, US. Compensation range: $101K - $300K.

Location Context

Across all AI roles, 16% (613 positions) offer remote work, while 3,187 require on-site attendance. Top AI hiring metros: New York (2,448 roles, $210,000 median); San Francisco (1,990 roles, $253,000 median); Los Angeles (1,686 roles, $189,000 median).

Career Path

Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.

From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.

The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.

What to Expect in Interviews

Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.

When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.

AI Hiring Overview

The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.

The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).

Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.

The AI Job Market Today

The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.

The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (119) are outnumbered by mid-level (1,813) and senior (1,472) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 420 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.

AI compensation is structured in clear tiers. The market median sits at $200,000. Top-quartile roles start at $253,000, and the 90th percentile reaches $307,500. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.

Category matters for compensation. AI Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $142,800. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.

The most in-demand skills across all AI postings: Python (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.

Frequently Asked Questions

Based on 223 roles with disclosed compensation, the median salary for Research Scientist positions is $223,400. Actual compensation varies by seniority, location, and company stage.
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
About 16% of the 3,824 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
Amazon.com is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from Research Scientist positions include Research Lead, Distinguished Scientist, VP of Research. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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