Senior Applied Scientist, Prime Video - Compression Efficiency Research Team

We need to output only HTML fragment, no html/body tags, no markdown fences. Use

for section headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. Include sections only if posting has real specific content. We need to parse the description. The description includes: - Intro about Prime Video (maybe "About the role"? Actually description includes overview of Prime Video and role description. Could be "About the role" or maybe "Responsibilities". The posting includes "Key job responsibilities" and "A day in the life". Also "Basic Qualifications", "Preferred Qualifications". Also salary range and benefits. We need to map to headings: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We need to decide which sections have content. - About the role: Could include the introductory paragraph describing Prime Video and the role's purpose. That seems appropriate. - Responsibilities: The "Key job responsibilities" and "A day in the life" sections contain responsibilities. - Requirements: Could be "Basic Qualifications" and maybe "Preferred Qualifications"? Usually Requirements = basic qualifications. Qualifications could be preferred? But we have both Requirements and Qualifications headings. We need to decide what to put where. The instruction: Use headings for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule). So we can have both Requirements and Qualifications sections. Likely Requirements = basic qualifications (must-have). Qualifications = preferred qualifications (nice-to-have). Skills could be extracted from qualifications? Might be redundant. But we can still include Skills if there is specific skill content. The posting mentions "Experience programming in Java, C++, Python or related language", "Experience with neural deep learning methods and machine learning", "Experience with Generative AI for image/video (e.g. diffusion)", "Experience with objective video quality measurement techniques", "Knowledge about defects in video and how to reduce such defects at scale". Those could go under Skills. But we must not create sections with filler text. So we need to ensure each section has real content. Let's extract content: About the role: The first paragraph(s) describing Prime Video and the role: "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!" That's good. Responsibilities: Combine "Key job responsibilities" bullet list and "A day in the life". Let's extract bullet points: Key job responsibilities: - The work would involve working with creation of ground-truth datasets, creating new video diffusion model architectures and training methodologies that ensure the best temporal consistency, preservation of creative intent, and perceptual quality. - You will also work on optimization and deployment of such models in production workflow and will define/measure suitable at-scale success criteria. - Aspects of work can involve scene understanding at a semantic level using latest techniques. - You would develop innovative solutions that achieve the best balance between speed vs performance, file invention disclosures, and publish these novel approaches in tier-1 conferences. - You would collaborate with research scientists with domain depth in video encoding/compression. - You would conduct subjective ratings tests to generate ground truth data for your models, when required. - You would also contribute to development of new video quality models that correlate highly with subjective ratings and help quantify the improvements brought about by your work. - You would define and refine team processes around ML/DL model development, deployment, and guardrail definition. A day in the life: - You will work with Video Research Scientists who will bring domain expertise to jointly define the specific problem and technical approach. - You may collaborate with academia through sponsored research programs on complex problems of long-term importance in your area of work. - You will interface with ML engineers to convert your output into production workflows. - You will help develop new AI workflows that are more efficient from a compute perspective. - You will work with product managers to develop product roadmap that align with business goals. - You will help hire new talent and will help develop talent through knowledge sharing and mentorship. We can combine these into a

• list. Requirements (Basic Qualifications): - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning Qualifications (Preferred Qualifications): - Experience with Generative AI for image/video (e.g. diffusion) - Experience with objective video quality measurement techniques - Knowledge about defects in video and how to reduce such defects at scale Skills: Could be derived from qualifications? Might be overlapping. But we could list technical skills: Java, C++, Python, deep learning, diffusion models, video quality measurement, video defect reduction, etc. However we already have them in qualifications. To avoid duplication, maybe we omit Skills section if no distinct content beyond qualifications. But we need to decide: The instruction says prefer a few substantive sections over many thin ones. So we could combine Requirements and Qualifications into one? But we have separate headings allowed. We could put Requirements = Basic Qualifications, Qualifications = Preferred Qualifications, and maybe omit Skills if no extra content. However we need to check if there is any skill-specific content not covered: The posting mentions "Experience programming in Java, C++, Python or related language" (skill), "Experience with neural deep learning methods and machine learning" (skill), "Experience with Generative AI for image/video (e.g. diffusion)" (skill), "Experience with objective video quality measurement techniques" (skill), "Knowledge about defects in video and how to reduce such defects at scale" (skill). Those could go under Skills. But then Requirements and Qualifications would be empty? We could instead treat Requirements as basic qualifications (education/experience), Qualifications as preferred qualifications (experience/knowledge), and Skills as specific technical skills (languages, tools). However the basic qualifications already include experience programming in Java, C++, Python etc. That's a skill. So maybe we put that under Skills, and keep Requirements as education/experience years, Qualifications as preferred experience/knowledge. Let's parse: Basic Qualifications: - 3+ years of building machine learning models for business application experience (experience) - PhD, or Master's degree and 6+ years of applied research experience (education+experience) - Experience programming in Java, C++, Python or related language (skill) - Experience with neural deep learning methods and machine learning (skill) Preferred Qualifications: - Experience with Generative AI for image/video (e.g. diffusion) (skill) - Experience with objective video quality measurement techniques (skill) - Knowledge about defects in video and how to reduce such defects at scale (skill) Thus we could have: Requirements: education/experience (first two bullets) Qualifications: preferred experience/knowledge (all three preferred) Skills: programming languages and deep learning experience (maybe also diffusion etc). But that would duplicate preferred qualifications. Better to keep Skills as programming languages and deep learning methods (Java, C++, Python, neural deep learning). Then Preferred Qualifications cover generative AI, video quality measurement, defects knowledge. Thus we need to split basic qualifications into Requirements (education/experience) and Skills (programming languages, deep learning). Let's do that. Requirements: - 3+ years of building machine learning models for business application experience - PhD, or Master's degree and 6+ years of applied research experience Skills: - Experience programming in Java, C++, Python or related language - Experience with neural deep learning methods and machine learning Qualifications (Preferred): - Experience with Generative AI for image/video (e.g. diffusion) - Experience with objective video quality measurement techniques - Knowledge about defects in video and how to reduce such defects at scale Now Benefits: The posting mentions benefits: "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." Also mentions sign-on payments and RSUs. That's compensation/benefits. We'll include Benefits section with that content. Pay: The posting includes salary range: "USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually". Also mentions base salary range, sign-on payments and RSUs. So we can include Pay section with that salary range and note about sign-on payments and RSUs. Schedule: No explicit schedule info (full-time implied). Not given. So we should not create Schedule section. Now we need to output HTML fragment with headings

  and content

  or

  • . Ensure we don't include boilerplate like EEO, accommodation, etc. Remove those lines. We must preserve all substantive information; do not invent or summarize away detail. So we need to keep details like "creation of ground-truth datasets", "creating new video diffusion model architectures", etc. Keep them exactly as in the posting (maybe slight rephrase but must preserve meaning). We'll keep them as is. We need to avoid duplication: The "Key job responsibilities" and "A day in the life" both contain responsibilities; we can combine them into a single list. Now produce HTML:

    About the role

    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!

    Responsibilities

    • The work would involve working with creation of ground-truth datasets, creating new video diffusion model architectures and training methodologies that ensure the best temporal consistency, preservation of creative intent, and perceptual quality.