applied scientist

applied scientist ii, prime video - personalization and discovery science, personalization and discovery science Jobs in New York

applied scientist ii, prime video - personalization and discovery science, personalization and discovery science

applied scientist, artificial general intelligence Jobs in New York

applied scientist, artificial general intelligence

applied scientist, creators Jobs in New York

applied scientist, creators

applied scientist, prime video - personalization and discovery science Jobs in New York

applied scientist, prime video - personalization and discovery science

machine learning scientist

Amazon Web Services

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
At Secure Work Enablement (SWE), we're pioneering breakthrough AI technologies that are fundamentally transforming how millions of teams and businesses work. Our mission combines leading machine learning research with Amazon's unparalleled expertise in enterprise computing and security to create the next generation of intelligent workplace solutions.<br>
<br>
Our portfolio encompasses four innovative domains where applied AI research is critical: Next-Generation End User Computing, where we're developing novel machine learning models for human-AI collaboration; Amazon One's advanced biometric systems; Secure Collaboration platforms Wickr and Chime; and Gaia &ndash; our revolutionary AI-native workspace that's redefining human-AI agent interactions. Each area presents unique opportunities for advancing the state-of-the-art in machine learning, natural language processing, and AI systems.<br>
<br>
We're at an inflection point where traditional workplace computing is being revolutionized by AI technologies. Our distinctive challenge lies in solving complex machine learning problems at scale while maintaining strict security requirements &ndash; from developing sophisticated ML models for secure information access to creating intelligent systems that can understand and enhance human productivity in real-time.<br>
<br>
With an accomplished team of 650+ technologists and multiple tier-1 services, we're seeking a Senior Principal Scientist to spearhead our AI research and development initiatives. This role offers the opportunity to tackle unprecedented challenges in applied machine learning, including:<br>
<br>
<ul><li>Developing novel AI architectures for secure, enterprise-grade collaborative systems</li><li>Advancing the science of human-AI interaction in workplace environments</li><li>Creating new frameworks for AI agent orchestration and optimization</li><li>Pioneering new approaches to privacy-preserving machine learning</li></ul><br>
Your scientific leadership will be crucial in defining and solving complex AI problems that will shape the future of work for years to come, working across multiple research teams and beyond SWE's boundaries.<br>
<br>
Key job responsibilities<br>
As a Senior Principal Scientist in Secure Work Enablement (SWE), you will have deep subject matter expertise in the area of large language models and generative AI across various modalities. You will work with multiple teams of scientists and engineers to translate business and functional requirements into concrete deliverables. You will invent new product experiences that enable teams and agents to collaborate effectively. You will have the opportunity to invent new approaches that help our customers achieve better results using natural language as the interface. Your inputs will shape the future of work.<br>
You will liaise with internal Amazon partners and work on bringing state-of-the-art LLM/GenAI models to production. You will stay abreast of the latest developments in the field of GenAI and identify opportunities to improve the efficiency and productivity of the team. You will define a long-term science vision for our business, driven by our customer&rsquo;s needs, and translate it into actionable plans for our team of applied scientists, and engineers. Finally, you will work with academic partners to support our in-house talent with direct access to leading research and mentoring.</div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>Graduate degree in Computer science/Math or related field.</li><li>Experience in building complex, real-time systems involving Agentic AI, Personalization and Reinforced Learning with successful delivery to customers. Demonstrated track record of project delivery for large, cross-functional projects with evolving requirements.
</li><li>Computer Science fundamentals in data structures, algorithm design and complexity analysis.
</li><li>Ability to develop machine learning platform strategy in the domain of recommender systems.
</li><li>Demonstrated track record of peer-reviewed scientific publications that advance state-of-the art for applied science.</li></ul><h2 class="jobSectionHeader"><b><br>
PREFERRED QUALIFICATIONS</b></h2><ul><li>15+ years of relevant, broad research experience after PhD degree or equivalent.</li><li>Ability to take a project from requirements gathering and design to actual product launch</li><li>Exceptional customer understanding skills including the ability to discover the true challenges to efficient product discovery, and experience in leading science efforts to meet timelines with optimal solutions. Deep expertise in Machine Learning as applied to large-scale generative models Proficiency in programming for algorithm and code reviews.</li><li>Strong core competency in mathematics and statistics.
</li><li>Track record of successful projects in algorithm design and product development.
</li><li>Publications at top-tier peer-reviewed conferences or journals.
</li><li>Strong prior experience with mentorship and/or management of senior scientists and engineers.
</li><li>Thinks strategically, but stays on top of tactical execution.
</li><li>Exhibits excellent business judgment; balances business, product, and technology very well.
</li><li>Effective verbal and written communication skills with non-technical and technical audiences. Experience working with real-world data sets and building scalable models from big data.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $240,100/year in our lowest geographic market up to $350,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Sr. Principal Scientist, Secure Work Enablement

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></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.<br>
<br>
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience.<br>
<br>
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.<br>
<br>
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!<br>
<br>
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.<br>
<br>
Key job responsibilities<br>
<ul><li>Develop AI solutions for various Prime Video Search 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><br>
About the team<br>
Prime Video Search Science team owns science solution to power search experience on various devices, from sourcing, relevance, ranking, to name a few. We work closely with the engineering teams to launch our solutions in production.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>3+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience building machine learning models or developing algorithms for business application</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Are enrolled in a PhD in computer science, machine learning, engineering, or related fields</li><li>Experience in search, advertising, recommendation systems or related domains;</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Prime Video - Personalization and Discovery Science

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Are you a passionate Applied Scientist (AS) ready to shape the future of digital content creation? At Amazon, we're building Earth's most desired destination for creators to monetize their unique skills, inspire the next generation of customers, and help brands expand their reach. We build innovative products and experiences that drive growth for creators across Amazon's ecosystem. Our team owns the entire Creator product suite, ensuring a cohesive experience, optimizing compensation structures, and launching features that help creators achieve both monetary and non-monetary goals.<br>
<br>
Key job responsibilities<br>
As an AS on our team, you will:<br>
<ul><li>Handle challenging problems that directly impact millions of creators and customers</li><li>Independently collect and analyze data</li><li>Develop and deliver scalable predictive models, using any necessary programming, machine learning, and statistical analysis software</li><li>Collaborate with other scientists, engineers, product managers, and business teams to creatively solve problems, measure and estimate risks, and constructively critique peer research</li><li>Consult with engineering teams to design data and modeling pipelines which successfully interface with new and existing software</li><li>Participate in design and implementation across teams to contribute to initiatives and develop optimal solutions that benefit the creators organization</li></ul><br>
The successful candidate is a self-starter, comfortable with a dynamic, fast-paced environment, and able to think big while paying careful attention to detail. You have deep knowledge of an area/multiple areas of science, with a track record of applying this knowledge to deliver science solutions in a business setting and a demonstrated ability to operate at scale. You excel in a culture of invention and collaboration.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 2+ years of CS, CE, ML or related field experience</li><li>Experience programming in Java, C++, Python or related language</li><li>2+ years of building models for business application experience</li><li>2+ years of hands-on predictive modeling and large data analysis experience</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience in designing experiments and statistical analysis of results</li><li>Experience in investigating, designing, prototyping, and delivering new and innovative system solutions</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Creators

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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.
<br>
<br>
Key job responsibilities<br>
This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to:<br>
<br>
<ul><li>Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.</li><li>Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.</li><li>Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.</li><li>Contribute to the enhancement of team&rsquo;s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 8+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li><li>Experience developing and deploying models in real-world production environments.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.</li><li>Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.</li><li>Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).</li><li>Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.</li><li>Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.</li><li>Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Senior Applied Scientist, Sponsored Products and Brands Off-Search

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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.
<br>
<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
<br>
Key job responsibilities<br>
This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to:<br>
<br>
<ul><li>Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.</li><li>Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.</li><li>Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.</li><li>Contribute to the enhancement of team&rsquo;s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 8+ years of applied research experience</li><li>3+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li><li>Experience developing and deploying models in real-world production environments.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.</li><li>Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.</li><li>Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).</li><li>Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.</li><li>Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.</li><li>Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
<br>
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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Sr. Applied Scientist, Sponsored Products and Brands Off-Search

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through state-of-the-art 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.
<br>
<br>
Curious about our advertising solutions? Discover more about Sponsored Products and Sponsored Brands to see how we&rsquo;re helping businesses grow on Amazon.com and beyond!<br>
<br>
Key job responsibilities<br>
This role will be pivotal in redesigning how ads contribute to a personalized, relevant, and inspirational shopping experience, with the customer value proposition at the forefront. Key responsibilities include, but are not limited to:<br>
<br>
<ul><li>Contribute to the design and development of GenAI, deep learning, multi-objective optimization and/or reinforcement learning empowered solutions to transform ad retrieval, auctions, whole-page relevance, and/or bespoke shopping experiences.</li><li>Collaborate cross-functionally with other scientists, engineers, and product managers to bring scalable, production-ready science solutions to life.</li><li>Stay abreast of industry trends in GenAI, LLMs, and related disciplines, bringing fresh and innovative concepts, ideas, and prototypes to the organization.</li><li>Contribute to the enhancement of team&rsquo;s scientific and technical rigor by identifying and implementing best-in-class algorithms, methodologies, and infrastructure that enable rapid experimentation and scaling.</li><li>Mentor and grow junior scientists and engineers, cultivating a high-performing, collaborative, and intellectually curious team.</li></ul><br>
A day in the life<br>
As an Applied Scientist on the Sponsored Products and Brands Off-Search team, you will contribute to the development in Generative AI (GenAI) and Large Language Models (LLMs) to revolutionize our advertising flow, backend optimization, and frontend shopping experiences. This is a rare opportunity to redefine how ads are retrieved, allocated, and/or experienced&mdash;elevating them into personalized, contextually aware, and inspiring components of the customer journey. You will have the opportunity to fundamentally transform areas such as ad retrieval, ad allocation, whole-page relevance, and differentiated recommendations through the lens of GenAI. By building novel generative models grounded in both Amazon&rsquo;s rich data and the world&rsquo;s collective knowledge, your work will shape how customers engage with ads, discover products, and make purchasing decisions. If you are passionate about applying frontier AI to real-world problems with massive scale and impact, this is your opportunity to define the next chapter of advertising science.<br>
<br>
About the team<br>
The Off-Search team within Sponsored Products and Brands (SPB) is focused on building delightful ad experiences across various surfaces beyond Search on Amazon&mdash;such as product detail pages, the homepage, and store-in-store pages&mdash;to drive monetization. Our vision is to deliver highly personalized, context-aware advertising that adapts to individual shopper preferences, scales across diverse page types, remains relevant to seasonal and event-driven moments, and integrates seamlessly with organic recommendations such as new arrivals, basket-building content, and fast-delivery options. To execute this vision, we work in close partnership with Amazon Stores stakeholders to lead the expansion and growth of advertising across Amazon-owned and -operated pages beyond Search. We operate full stack&mdash;from backend ads-retail edge services, ads retrieval, and ad auctions to shopper-facing experiences&mdash;all designed to deliver meaningful value.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>3+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Strong foundation in GenAI, large language models, machine learning, deep learning, probabilistic modeling, and/or optimization.</li><li>Experience developing and deploying models in real-world production environments.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Proven expertise in Generative AI, foundation models, LLMs, and/or fine-tuning and customization for downstream tasks.</li><li>Hands-on experience in ads ranking, retrieval, recommendation systems, search, or personalization at web scale.</li><li>Deep understanding of multi-modal modeling, few-shot learning, retrieval-augmented generation (RAG), or reinforcement learning from human feedback (RLHF).</li><li>Experience with online experimentation, A/B testing frameworks, and metrics design for advertising or e-commerce.</li><li>Demonstrated ability to communicate complex technical topics clearly to both technical and non-technical audiences.</li><li>Experience in computational advertising, including familiarity with auction theory, ad economics, and advertiser performance metrics.</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
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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.<br>
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Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Sponsored Products - Off-Search

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
The Artificial General Intelligence (AGI) team is looking for a passionate, talented, and inventive Applied Scientist to work on pre-training methodologies for Generative Artificial Intelligence (GenAI) models. You will interact closely with our customers and with the academic and research communities.<br>
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Key job responsibilities<br>
Join us to work as an integral part of a team that has experience with GenAI models in this space. We work on these areas:<br>
<ul><li>Scaling laws</li><li>Hardware-informed efficient model architecture, low-precision training</li><li>Optimization methods, learning objectives, curriculum design</li><li>Deep learning theories on efficient hyperparameter search and self-supervised learning
</li><li>Learning objectives and reinforcement learning methods</li><li>Distributed training methods and solutions</li><li>AI-assisted research</li></ul><br>
About the team<br>
The AGI team has a mission to push the envelope in GenAI with Large Language Models (LLMs) and multimodal systems, in order to provide the best-possible experience for our customers.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>1+ years of building models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>PhD in Computer Science, Electrical Engineering, Mathematics or related field</li><li>Strong experience with Generative Artificial Intelligence (GenAI) technologies and Large Language Models (LLMs)</li><li>Experience with patents or publications at top-tier peer-reviewed conferences or journals</li><li>Experience with popular deep learning frameworks, including PyTorch</li></ul><br>
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.<br>
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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.<br>
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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.<br>
<br>
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, Artificial General Intelligence

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