2026 fall applied science internship - gen ai & large language models - united states, phd student science recruiting

aiml - applied ml engineer, data generation & verification

2026 fall applied science internship - gen ai & large language models - united states, phd student science recruiting Jobs in Seattle

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aiml - applied ml engineer, data generation & verification Jobs in Seattle

senior applied scientist ai evaluation quality systems

Apple

Apple Services Engineering (ASE) powers the AI and LLM features behind experiences that hundreds of millions of users love every day. As these systems increasingly rely on human-in-the-loop evaluation, the quality of our products is directly constrained by the quality of our evaluation systems. We believe that to build exceptional AI, you need exceptional mechanisms to validate the signals used to train and evaluate them. 
 
Description 
 
The Human-centered AI, Data Quality Operations team is looking for a Senior Applied Scientist to join our growing team. We are building the systems and methodologies that make AI evaluation trustworthy, and scalable - directly shaping how Apple develops and validates AI across products and services. In this role, you will develop novel, scalable quality control solutions, working closely with cross-functional teams to ensure the data powering our AI/ML systems meets the highest standards of accuracy, consistency, and relevance. 
 
Your work will span two connected problem spaces. The first is the methodology and tooling that generates reliable ground truth and detects quality failures across human annotation and automated evaluation pipelines. The second is the autonomous QA agents that make those methodologies generalizable across teams and use cases. This role demands fluency across research thinking and engineering execution - you will prototype, validate, and ship. A strong point of view on when not to use a model or agent is as valued here as the ability to build one. 
 
&quot;,&quot;responsibilities&quot;:&quot;Design and implement scalable ground truth generation pipelines across varied task types, annotation modalities, and cold start conditions 
 
Build and maintain calibration frameworks that keep LLM evaluators anchored to human judgment over time 
 
Develop anomaly detection systems that surface evaluator drift, distribution shifts, and coverage gaps across human annotation and automated evaluation pipelines 
 
Design, build, and deploy autonomous QA agents targeting specific facets of evaluation quality, architected for generalizability and self-service adoption across teams 
 
Partner closely with cross-functional teams to ensure evaluation systems meet the highest standards of accuracy, consistency, and relevance 
 
Communicate findings and recommendations clearly to both technical and non-technical stakeholders, including senior leadership 
 
Contribute to a culture of technical excellence by sharing knowledge and best practices across the team 
 
Preferred Qualifications 
 
PhD in Computer Science, Machine Learning, Statistics, or a related field 
 
Experience designing agent architectures that are configurable and extensible by practitioners who did not build them 
 
Hands-on experience building anomaly detection systems for evaluation quality, including drift detection, distribution analysis, and systematic bias identification 
 
Strong communication skills with the ability to influence technical direction across cross-functional teams 
 
Demonstrated passion for leveraging AI to improve work efficiency and scale 
 
Minimum Qualifications 
 
5+ years of industry experience in applied science or machine learning with demonstrated impact on shipped systems 
 
Strong hands-on experience with Large Language Models including prompt engineering and applied use cases such as grading, validation, or classification 
 
Strong working knowledge of evaluation methodology for generative AI, including LLM-as-a-judge design, meta-evaluation, and failure mode analysis 
 
Familiarity with human-in-the-loop evaluation systems and the operational dynamics that affect data quality at scale 
 
Hands-on experience designing ground truth generation pipelines across varied task types and annotation modalities 
 
Proficiency in Python and relevant ML frameworks, with production experience building, deploying, and monitoring LLM-based pipelines and agents 
 
MS or PhD in Computer Science, Machine Learning, Statistics, or a related quantitative field, or equivalent practical experience 
 
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant . 
 
Pay &amp; Benefits 
 
At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $139,500 and $258,100, and your base pay will depend on your skills, qualifications, experience, and location. 
 
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. 
 
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Senior Applied Scientist - AI Evaluation & Quality Systems

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. 
 
We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. 
As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
Key job responsibilities 
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. 
Specific responsibilities include: 
<ul><li>Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features</li><li>Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings</li><li>Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases</li><li>Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance</li><li>Develop and refine annotation guidelines and quality frameworks for evaluation tasks</li><li>Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies</li><li>Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements</li><li>Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts</li><li>Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets</li></ul> 
About the team 
 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Hybrid Work 
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of working with or evaluating AI systems experience</li><li>1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience</li><li>Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul> 
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&rsquo;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&rsquo;re applying in isn&rsquo;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 &amp; AD&amp;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, Santa Clara - 157,300.00 - 212,800.00 USD annually 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, AWS Quick Data

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through novel generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace ecosystem. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising.
 
 
Key job responsibilities 
As a Senior Applied Scientist on our team, you will 
 
<ul><li>Develop AI solutions for Sponsored Brands advertiser and shopper experiences. Build recommendation systems that leverage generative models to develop and improve campaigns.</li><li>You invent and design new solutions for scientifically-complex problem areas and/or opportunities in new business initiatives.</li><li>You drive or heavily influence the design of scientifically-complex software solutions or systems, for which you personally write significant parts of the critical scientific novelty. You take ownership of these components, providing a system-wide view and design guidance. These systems or solutions can be brand new or evolve from existing ones.</li><li>Define a long-term science vision and roadmap for our Sponsored Brands advertising business, driven from our customers' needs, translating that direction into specific plans for applied scientists and engineering teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.</li><li>Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end;</li><li>Design and conduct A/B experiments to evaluate proposed solutions based on in-depth data analyses;</li><li>Think big about the arc of development of Gen AI over a multi-year horizon, and identify new opportunities to apply these technologies to solve real-world problems</li><li>Effectively communicate technical and non-technical ideas with teammates and stakeholders;</li><li>Translate complex scientific challenges into clear and impactful solutions for business stakeholders.</li><li>Mentor and guide junior scientists, fostering a collaborative and high-performing team culture.</li><li>Stay up-to-date with advancements and the latest modeling techniques in the field
</li></ul> 
About the team 
We are on a mission to make Amazon the best in class destination for shoppers to discover, engage, and purchase relevant products, from brands that are relevant to them. In this role, you will design and implement Gen AI solutions that help millions of advertisers create more effective ad campaigns with intelligent recommendations, while improving the overall experience at Amazon's global scale.
</div><h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>3+ years of building machine learning models for business application experience</li><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
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&rsquo;re applying in isn&rsquo;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 &amp; AD&amp;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 
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually</div>

Senior Applied Scientist, Sponsored Products and Brands

Alignerr

<div>
 
 About The Role
 
 
 
 We're looking for experienced entrepreneurship educators and business experts to help shape how AI understands startups, innovation, and business planning. Your real-world knowledge will directly influence the quality and accuracy of AI systems used by millions &mdash; making this one of the most impactful freelance opportunities available to business educators today.
 
 
 <ul>
 <li>
 Organization: Alignerr (Powered by Labelbox)
 </li>
 <li>
 Type: Hourly Contract
 </li>
 <li>
 Location: Remote
 </li>
 <li>
 Commitment: 10&ndash;40 hours/week
 
 
 </li>
 </ul>
 
 What You'll Do
 
 
 
 <ul>
 <li>
 Review AI-generated startup and entrepreneurship scenarios for accuracy and practical relevance
 </li>
 <li>
 Assess business models, go-to-market strategies, and early-stage assumptions
 </li>
 <li>
 Identify unrealistic financial projections, logical gaps, or flawed reasoning
 </li>
 <li>
 Provide structured, actionable feedback that improves AI training quality
 </li>
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 Work independently and asynchronously &mdash; on your own schedule
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 3+ years of experience teaching entrepreneurship, small business, or startup strategy
 </li>
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 Strong grasp of business model frameworks and early-stage decision-making
 </li>
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 Able to critically evaluate written business plans and scenario-based content
 </li>
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 Comfortable delivering clear, applied, real-world feedback in writing
 </li>
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 Self-motivated and reliable when working independently
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 MBA or graduate degree with an entrepreneurship focus
 </li>
 <li>
 Founder, operator, or startup advisor experience
 </li>
 <li>
 Familiarity with AI systems or content evaluation workflows
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Work on cutting-edge AI projects with top research labs
 </li>
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 Fully remote and flexible &mdash; work on your own schedule
 </li>
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 Freelance perks: autonomy, variety, and global collaboration
 </li>
 <li>
 Contribute to meaningful work that shapes how AI understands business and innovation
 </li>
 <li>
 Potential for ongoing work and contract extension
 </li>
 </ul>
</div>

Entrepreneurship Instructor (AI Training)

<div>
 
 About The Role
 
 
 
 We&rsquo;re looking for experienced postsecondary Business instructors to help evaluate and improve AI systems trained on core business concepts and real-world decision-making.
 
 
 <ul>
 <li>
 Organization: Alignerr (Powered by Labelbox)
 </li>
 <li>
 Location: Remote
 </li>
 <li>
 Type: Hourly / Task-based Contract
 </li>
 <li>
 Compensation: $35-70 /hour
 </li>
 <li>
 Commitment: 10-40 hours/week
 
 
 </li>
 </ul>
 
 What You&rsquo;ll Do
 
 
 
 <ul>
 <li>
 Design and review business questions and scenarios used in AI training.
 </li>
 <li>
 Evaluate the accuracy, clarity, and practical relevance of AI-generated business content.
 </li>
 <li>
 Provide structured feedback to improve reasoning, explanations, and examples.
 </li>
 <li>
 Apply real-world teaching experience to validate scenarios and edge cases.
 </li>
 <li>
 Work independently and asynchronously to meet project deadlines.
 
 
 </li>
 </ul>
 
 Who You Are
 
 
 
 <ul>
 <li>
 3+ years of experience teaching business at the postsecondary level.
 </li>
 <li>
 Strong understanding of core business topics (management, strategy, operations, finance basics).
 </li>
 <li>
 Able to clearly explain and evaluate business reasoning in written form.
 </li>
 <li>
 Comfortable reviewing structured content and providing detailed feedback.
 
 
 </li>
 </ul>
 
 Nice to Have
 
 
 
 <ul>
 <li>
 Master&rsquo;s degree in Business, Management, or related field.
 </li>
 <li>
 Industry or applied business experience.
 </li>
 <li>
 Familiarity with AI or content evaluation workflows.
 
 
 </li>
 </ul>
 
 Why Join Us
 
 
 
 <ul>
 <li>
 Competitive pay and flexible remote work.
 </li>
 <li>
 Lead a team working on cutting-edge AI projects.
 </li>
 <li>
 Exposure to advanced LLMs and how they&rsquo;re trained.
 </li>
 <li>
 Freelance perks: autonomy, flexibility, and global collaboration.
 </li>
 <li>
 Potential for contract extension.
 
 
 </li>
 </ul>
 
 Application Process (Takes 10-15 min)
 
 
 
 <ul>
 <li>
 Submit your resume
 </li>
 <li>
 Complete a short screening
 </li>
 <li>
 Project matching and onboarding
 
 
 </li>
 </ul>
 
 PS: Our team reviews applications daily. Please complete your AI interview and application steps to be considered for this opportunity.
 
</div>

Business Teacher (Postsecondary – AI Training)

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
About Sponsored Products and Brands 
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you're energized by solving complex challenges and pushing the boundaries of what's possible with AI, join us in shaping the future of advertising. 
 
About our team 
The SPB Offsite team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third party sites where shoppers search and discover products. We use industry leading machine learning, high scale low latency systems, and AI technologies to create better sponsored customer experiences off the store. This role will have deep interest in building the next innovations in ad tech and shopping wherever shoppers go. You will work with external and internal partners to connect ad tech systems, understand customers, and drive results at scale. You are a deeply technical leader who operates with a GenAI first approach to product, engineering, and science based solutions. 
 
As an Applied Scientist on this team, you will:
 
<ul><li>Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.</li><li>Perform hands-on analysis and modeling of enormous data sets to develop insights that increase traffic monetization and merchandise sales, without compromising the shopper experience.</li><li>Build machine learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.</li><li>Run A/B experiments, gather data, and perform statistical analysis.</li><li>Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.</li><li>Research new and innovative machine learning approaches.</li></ul> 
Why you will love this opportunity: Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon&rsquo;s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate. 
 
Impact and Career Growth: You will invent new experiences and influence customer-facing shopping experiences to help suppliers grow their retail business and the auction dynamics that leverage native advertising; this is your opportunity to work within the fastest-growing businesses across all of Amazon! Define a long-term science vision for our advertising business, driven from our customers' needs, translating that direction into specific plans for research and applied scientists, as well as engineering and product teams. This role combines science leadership, organizational ability, technical strength, product focus, and business understanding.</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>3+ years of building models for business application experience</li><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience in professional software development</li><li>Experience in search advertising, search marketing, performance advertising, or similar digital advertising</li><li>Strong technical fluency in Generative AI</li><li>Deep understanding of large language models (LLMs), model fine tuning and prompt engineering</li><li>Ph.D. in computer science, mathematics, statistics, machine learning or equivalent quantitative field</li></ul> 
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&rsquo;re applying in isn&rsquo;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 &amp; AD&amp;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 - 172,400.00 - 223,400.00 USD annually 
USA, VA, Arlington - 142,800.00 - 193,200.00 USD annually 
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist, Sponsored Products

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
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 &ndash; 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&rsquo;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&rsquo;ll get to work on projects that are fast-paced, challenging, and varied. You&rsquo;ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. 
 
We&rsquo;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! 
 
We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. 
 
Key job responsibilities 
<ul><li>Develop AI solutions for various Prime Video Recommendation and Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods;</li><li>Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end;</li><li>Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses;</li><li>Effectively communicate technical and non-technical ideas with teammates and stakeholders;</li><li>Stay up-to-date with advancements and the latest modeling techniques in the field;</li><li>Publish your research findings in top conferences and journals.</li></ul> 
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 &amp; 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.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>5+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
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&rsquo;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&rsquo;re applying in isn&rsquo;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 &amp; AD&amp;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, NY, New York - 183,800.00 - 248,700.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

Sr. Applied Scientist, Prime Video - Personalization and Discovery Science

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