2026 1l patent litigation fellowship (dual summer) Jobs in Seattle

2026 1l patent litigation fellowship (dual summer)

2026 phd software engineer intern (machine learning), united states Jobs in Seattle

2026 phd software engineer intern (machine learning), united states

machine learning graduate (ecommerce user growth & intelligent marketing) - 2026 start (bs/ms) Jobs in Seattle

machine learning graduate (ecommerce user growth & intelligent marketing) - 2026 start (bs/ms)

senior software engineer

software engineer iii – new glenn, ai & robotics Jobs in Seattle

software engineer iii – new glenn, ai & robotics

2026 phd software engineer intern machine learning united states

Uber

<div>We're looking for PhD candidates in the machine learning and optimization domain to intern with a variety of teams during summer 2026 (12 weeks). You will be embedded in an engineering team and work closely with other specialists, data scientists, and product managers. As a PhD intern, you will work on an exciting yet bold problem independently, under the supervision of an experienced engineer on that team.
<br>
<br>
<b>About the Role
</b><br>
<br>
At Uber, we work on many ambitious engineering products covering many lines of business as well as the underlying platform technologies that power those businesses. We foster growth and increase profitability of Uber by pushing the frontiers of machine learning, constrained optimization, statistics, data science and economics and developing highly reliable and scalable platforms to accelerate Uber's impact on the transportation industry.
<br>
<br>
As a PhD software engineer intern, you will have a lot of opportunities to work with product managers, data scientists and, of course, engineers from different teams. You will have an opportunity to learn how to iterate over a product for greater success while demonstrating your area of expertise (machine learning, statistics, constrained optimization, distributed system, etc.). This is a unique opportunity to grow your skills with real-world experience and do highly impactful, yet fun work at the same time. It is an ambitious yet rewarding job!
<br>
<br>
<b>Team Options
</b><ul><li>The <b>Delivery Marketplace: Consumer and Courier Pricing, Matching and Logistics </b>is responsible for building the core technology across the delivery line of business including food delivery, grocery, and retail last mile. These include a diverse set of transformational projects and impactful products ranging from finding the optimal match between jobs and earners in the delivery space, to setting optimal prices for Eaters and Couriers. The organization is formed of talented teams of engineers and scientists working side by side on the state of the art innovations on the matching objective function, pricing algorithms, and promotions. To achieve these goals, we leverage big data tools and apply advanced machine learning models to drive top line and bottom line business outcomes.
</li><li>The <b>Trusted Identity org </b>inspires trust in the Uber business cycle through verified and authentic identities. The Account Integrity team prevents fake identities from operating on the platform, and ensures that accounts are not duplicated nor fraudulent to enhance accountability. The Identity Verification team ensures accounts are created by real humans by verifying their attributes. The Account Security team is responsible for defending account holders from fraud related to phishing and ATO (account takeover) attempts. The Device Intelligence team is responsible for collecting device signals that are critical for the other teams to reliably achieve their goals.
</li><li>The Uber <b>Risk engineering team </b>is tackling challenges related to fraud and abuse detection. Our work is crucial in maintaining the integrity of Uber's platform. The team employs advanced machine learning including LLMs and computer vision, knowledge graph, similarity search and reinforcement learning to monitor transactions, detect unusual patterns, and implement robust verification methods
</li><li>The <b>Mobility Matching team </b>at Uber plays a crucial role in developing and optimizing algorithms and systems that match supply (drivers) with demand (riders) in real-time. You will work on complex problems, leveraging data and build ML algorithms to ensure efficient and reliable marketplace matching. The team is broadly part of the Marketplace (PIMS) org, a central pillar to Uber's core technology which includes pricing, incentives/investments, matching, surge, etc. As the key brain of the company, we manage the complex dynamics of supply and demand, optimize dispatching algorithms, and continuously innovate to enhance the overall user experience for both riders and drivers. Improvements in these systems increase revenue in the hundreds of millions of dollars, and decrease wasted time of drivers and users. Your contributions will directly impact the experience of millions of users worldwide.
</li><li>The <b>Rider Pricing and Incentives team </b>at Uber plays a crucial role in developing and optimizing algorithms and systems that determine the trip prices, discounting and promotions for Uber riders worldwide. You will work on complex modeling, pricing and incentives targeting problems, leveraging data and building ML algorithms to ensure accurate and robust pricing models and successful pricing optimization outcomes. The team is broadly part of the Marketplace organization, a central pillar to Uber's core technology which more broadly includes pricing, incentives/investments, matching, surge, etc. As a key team within Uber, we manage the complex dynamics between short term optimized pricing and long-term optimized pricing, promotion targeting and continuously innovating to enhance the overall user experience for riders. Improvements in these systems increase revenue in the hundreds of millions of dollars, and positively impact the experience of millions of users worldwide, as well as their ability to get around in the world.
</li><li>Join our <b>Capacity Planning team </b>as a Ph.D. intern to drive the future of infrastructure resource management through advanced quantitative methods. You will be at the forefront of implementing our data-driven forecasting vision, moving away from reactive, manual processes to scalable, automated solutions that utilize predictive analytics and real-time utilization data. This is a high-impact opportunity to work with the Applied Science and Engineering teams on designing and optimizing the central intelligence systems for capacity planning. Your expertise will be crucial in developing granular, highly accurate resource forecasts, ensuring service reliability for unexpected demand, and making key decisions that directly influence financial accountability, operational agility, and optimal resource utilization across the entire platform.
</li><li>The <b>Autonomous Vehicles Cloud team </b>is dedicated to accelerating the autonomous vehicles industry to L4 by serving as a premier AV data leader. Recently, we announced a partnership with NVIDIA to jointly develop a data factory for autonomous vehicle development. The team includes engineers with diverse backgrounds in embedded software, cloud computing, batch data processing, and ML research. We are looking for talent passionate about autonomous vehicles and eager to make a significant impact.
</li><li>The <b>Marketplace Signals </b>team at Uber is responsible for building and optimizing foundational marketplace signals that power user experiences and drive marketplace efficiency. Our team ensures that key signals-such as eyeball ETA, spinner time, and supply reliability indicators-are leveraged effectively across various Uber products and levers, enabling data-driven decision-making and seamless coordination across different business functions.
</li><li><b>Applied AI </b>is a horizontal AI team at Uber partnering with product and platform teams across the company to deliver cutting-edge machine learning solutions for core business problems. The Computer Vision team in AppliedAI specializes in Generative AI, Foundation Model, and classical Computer Vision solutions, and the ML infrastructure needed to scale these systems in production.
</li><li><b>Fabric Controller </b>brings together platforms that keep large scale systems resilient and easy to operate, including Cadence and Repair Engine. Cadence is an open source workflow orchestration engine that manages distributed state, retries, scaling, and recovery so teams can focus on business logic while supporting mission critical workloads across many industries. Repair Engine detects, diagnoses, and remediates issues by correlating signals across infrastructure and application layers through an ingestion pipeline and statistical analysis. An ML engine is being developed to improve diagnostics by learning patterns from historic issues, reducing false positives, and incorporating broader context such as workload types and traffic trends. Together these systems strengthen reliability, automation, and operational efficiency across the stack.
</li></ul><b>What You'll Do
</b><ul><li>Drive exciting, ambitious, previously unsolved projects from end to end
</li><li>Develop novel algorithms that use Uber data at global scale
</li><li>Thrive in an environment with ambiguous product requirements
</li><li>Collaborate closely with product managers and data scientists
</li><li>Be motivated to independently own and drive projects forward
</li><li>Have a passion to make Uber better for our customers
</li></ul><b>Basic Qualifications
</b><ul><li>Currently enrolled in a Ph.D. program studying computer science, machine learning, data mining, artificial intelligence, constrained optimization, statistics, or a related quantitative field
</li><li>Candidates must have at least one semester/quarter of their education left following the internship
</li><li>Knowledge of underlying technical foundations of statistics, machine learning, optimization, systems, etc.
</li><li>Experience in one or more object-oriented languages, including C++, Java, Python, or Go
</li></ul><b>Preferred Qualifications
</b><ul><li>Ability to communicate effectively with both technical and business partners
</li><li>Experience in simplifying/converting business problems into technical problems
</li>Research mentality with a bias towards action to structure a project from idea to experimentation to prototype to implementation<br>
<li>
</li></ul><br>
<br>
For New York, NY-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For San Francisco, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Seattle, WA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For Sunnyvale, CA-based roles: The base hourly rate amount for this role is USD$67.00 per hour. For all US locations, you will also be eligible for various benefits.</div>

2026 PhD Software Engineer Intern (Machine Learning), United States

Amazon.com

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company&rsquo;s Think Big leadership principle to the limits. If you&rsquo;re interested in innovating at scale to address big challenges in the world, this is the team for you.
<br>
<br>
As an Applied Scientist on our team, you will focus on building state-of-the-art ML models for biology. Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.<br>
<br>
Key job responsibilities<br>
<ul><li>Build, adapt and evaluate ML models for life sciences applications</li><li>Collaborate with a cross-functional team of ML scientists, biologists, software engineers and product managers</li></ul></div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD in computer science, machine learning, engineering, or related fields</li><li>Experience with programming languages such as Python, Java, C++</li><li>Expert knowledge of machine learning and deep learning; experience in applying ML to protein biology.</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience using Unix/Linux</li><li>Experience in professional software development</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</li><li>Expert knowledge of protein biology and design.</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, Special Projects

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
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 bridge human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights.<br>
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<br>
<br>
SPB Global Optimization (GO) team was created recently to accelerate GMSP growth in non-US markets. We are helping drive profitability across all marketplaces by creating delightful experiences for shoppers and advertisers alike. We are working backwards from customers to re-imagine Amazon's advertising stack from the ground up, leveraging multilingual and multi-modal GenAI technologies including semantic hash designs, LLMs, and more to deliver solutions that scale worldwide from day one. This is your opportunity to be part of a small, high-impact team that prototypes, invents, and ships state-of-the-art solutions that will define the future of digital advertising. 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>
<br>
<br>
Key job responsibilities<br>
<ul><li>Lead a cross-functional team of Applied Scientists, Machine Learning Engineers, and Software Development Engineers in delivering GMSP acceleration across multiple EU markets.
</li><li>Understand the unique needs of advertisers and shoppers in diverse marketplaces to craft the vision and milestones for SPB GO program in EU to create delightful experiences that increase engagement and satisfaction for both customer groups.</li><li>Architect next-generation systems that replace legacy monolithic infrastructure with scalable, intelligent solutions that scale worldwide on day one.
</li><li>Pioneer breakthrough applied science in multi-modal GenAI applications for advertising, combining text, image, and multi-lingual support.</li><li>Drive end-to-end innovation from research ideation through production deployment at Amazon scale.</li><li>Hire and develop top talent, providing technical direction and career growth guidance to scientists and engineers within and across organizations.</li></ul><br>
Your contributions will be highly visible and instrumental in hitting goals carried by Amazon's leadership team (S-Team). A diverse group of stakeholders will rely on your vision and messaging, including advertisers, agencies, and internal ad sales and operations teams.</div><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)</li><li>8+ years of building large-scale machine learning and AI solutions at Internet scale experience</li><li>Experience building large-scale machine learning and AI solutions at Internet scale</li><li>Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives</li><li>Experience hiring and leading experienced scientists as well as having a successful record of developing junior members from academia or industry to a successful career track</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)</li><li>10+ years of practical work applying ML to solve complex problems for large-scale applications experience</li><li>Experience in practical work applying ML to solve complex problems for large scale applications</li><li>Experience working with big data, machine learning and predictive modeling</li><li>Experience with big data technologies such as AWS, Hadoop, Spark, Pig, Hive etc.</li><li>Experience with Java, C++, or other programming language, as well as with R, MATLAB, Python, or an equivalent scripting language</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 $196,900/year in our lowest geographic market up to $340,300/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. Manager, Applied Science, Sponsored Products and Brands

ByteDance

<b>Location:</b><br>
Seattle
<br><br>
<b>Team:</b><br>
Technology
<br><br>
<b>Employment Type:</b><br>
Regular
<br><br>
<b>Job Code:</b><br>
A237244
<br><br>
Responsibilities
<br><br>
<b>Team Introduction:</b><br>
Our E-commerce Recommendation and Marketing Team is responsible for intelligent marketing and user growth for TikTok’s international e-commerce business across multiple global regions, including the US, Europe, Latin America, and Southeast Asia, and is accountable for both e-commerce scale and user base growth.
<br><br>
We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with ByteDance
<br><br>
Successful candidates must be able to commit to an onboarding date by end of year 2026.
<br><br>
Please state your availability and graduation date clearly in your resume.
<br>Applications will be reviewed on a rolling basis - we encourage you to apply early.
<br><br>
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to ByteDance and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
<br><br>
<b>Responsibilities:</b><br>
<ul>
<li>Build a full lifecycle user data and value system to address core pain points and business challenges in e-commerce user growth.</li>
<li>Participate in developing an industry-leading online marketing inference algorithm engine that integrates signals from search, recommendation, and marketing, moving from isolated decision-making in each domain to joint decision-making across domains.</li>
<li>Optimize international e-commerce user growth and intelligent marketing by improving the cost-effectiveness of key budget spending through algorithms — including subsidy distribution, product pricing, budget allocation, and traffic strategies — to enhance subsidy and traffic efficiency, ultimately driving GMV growth.</li>
</ul>
Qualifications
<br><br>
Minimum Qualifications
<br><ul>
<li>Bachelor's degree or above, graduating in 2026, preferably in Artificial Intelligence, Machine Learning, Computer Science, Mathematics, Operations Research, or related fields with 0-1 year of work experience</li>
<li>Solid foundation in algorithms and data structures, with strong programming skills.</li>
<li>Strong learning ability, curiosity, communication, and teamwork skills.</li>
<li>Solid foundation in machine learning algorithms, familiar with one or more of the following: machine learning, deep learning, causal inference, reinforcement learning.</li>
</ul>
Preferred Qualifications
<br><ul>
<li>Publications in top AI conferences/journals, or strong performance in ACM / machine learning competitions.</li>
<li>Research or project experience in user growth, intelligent marketing, or advertising; experience in LTV prediction, uplift modeling, operations research, sequence modeling, or multi-scenario modeling optimization.</li>
</ul>
Job Information
<br><br>
【For Pay Transparency】Compensation Description (Annually)
<br><br>
The base salary range for this position in the selected city is $112725 - $177840 annually.
<br><br>
Compensation may vary outside of this range depending on a number of factors, including a candidate’s qualifications, skills, competencies and experience, and location. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.
<br><br>
Benefits may vary depending on the nature of employment and the country work location. Employees have day one access to medical, dental, and vision insurance, a 401(k) savings plan with company match, paid parental leave, short-term and long-term disability coverage, life insurance, wellbeing benefits, among others. Employees also receive 10 paid holidays per year, 10 paid sick days per year and 17 days of Paid Personal Time (prorated upon hire with increasing accruals by tenure).
<br><br>
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
<br><br>
<b>For Los Angeles County (unincorporated) Candidates:</b><br>
Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state, and local laws including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Our company believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment:
<br><br>
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
<br><br>
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
<br><br>
3. Exercising sound judgment.
<br><br>
About Us
<br><br>
Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.
<br><br>
Why Join ByteDance
<br><br>
Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.
<br><br>
As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.
<br><br>
Diversity & Inclusion
<br><br>
ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.
<br><br>
Reasonable Accommodation
<br><br>
ByteDance is committed to providing reasonable accommodations in our recruitment processes for candidates with disabilities, pregnancy, sincerely held religious beliefs or other reasons protected by applicable laws. If you need assistance or a reasonable accommodation, please reach out to us at https://tinyurl.com/RA-request

Machine Learning Graduate (eCommerce User Growth & Intelligent Marketing) - 2026 Start (BS/MS)

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><div>
Innovators wanted! Are you an entrepreneur? A builder? A dreamer? This role is part of an Amazon Special Projects team that takes the company&rsquo;s Think Big leadership principle to the limits. If you&rsquo;re interested in innovating at scale to address big challenges in the world, this is the team for you.
<br>
<br>
Our team rewards curiosity while maintaining a laser-focus in bringing products to market. Competitive candidates are responsive, flexible, and able to succeed within an open, collaborative, entrepreneurial, startup-like environment. At the forefront of both academic and applied research in this product area, you have the opportunity to work together with a diverse and talented team of scientists, engineers, and product managers and collaborate with other teams.<br>
<br>
We are seeking a Principal Applied Scientist working on machine learning applications in life sciences. This role combines scientific leadership with hands-on innovation, driving solutions from exploratory research through production-ready solutions deployment, while maintaining high scientific standards. You will work with Amazon's large-scale computing resources to accelerate advances in machine learning applications.<br>
<br>
Key job responsibilities<br>
<ul><li>Lead ML for life science efforts using computational design approaches and ML-based tools.</li><li>Guide teams in applying SOTA ML methods, experimentation design, and modeling approaches.</li><li>Transform complex real world problems into scientific challenges and allocate resources effectively.</li><li>Review requirements, conduct technical architecture reviews, and make informed judgments around technical and business tradeoffs.</li><li>Provide mentorship to Applied Scientists, Research Scientists and Data Scientists while maintaining scientific rigor.</li><li>Collaborate with cross functional teams.</li></ul></div><h2 class="jobSectionHeader"><b><br>
BASIC QUALIFICATIONS</b></h2><ul><li>Deep expertise in machine learning, with broad knowledge across biology and life science.</li><li>Strong understanding of scientific methodologies and experimental design.</li><li>Ability to develop production-level code and systems.</li><li>Track record of working with cross-functional scientific teams and fostering collaboration.</li><li>10+ years of relevant, broad research experience after a PhD degree in computer science, computational biology or relevant field .</li></ul><h2 class="jobSectionHeader"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience with deep learning frameworks (PyTorch, TensorFlow).</li><li>Familiarity with high-performance computing environments.</li><li>Experience with ML for science and structural biology tools.</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 $179,000/year in our lowest geographic market up to $309,400/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>

Principal Applied Scientist, Amazon Special Projects

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
About Amazon Advertising:<br>
Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you&rsquo;re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you&rsquo;ve come to the right place.<br>
<br>
About our team:<br>
Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods.<br>
<br>
Key job responsibilities<br>
We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. The role will focus on developing predictive creative recommendations along with insights to improve campaign performance and creative generation process. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></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"><b>
PREFERRED QUALIFICATIONS</b></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><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, Creative X - RAPID

<div><h2 class="jobSectionHeader"><b>DESCRIPTION</b></h2><p>
About Amazon Advertising:<br>
Amazon Advertising operates at the intersection of eCommerce and advertising, offering a rich array of digital display advertising solutions with the goal of helping our customers find and discover anything they want to buy. We help advertisers of all types to reach Amazon customers on Amazon.com, across our other owned and operated sites, on other high quality sites across the web, and on millions of mobile devices. We start with the customer and work backwards in everything we do, including advertising. If you&rsquo;re interested in joining a rapidly growing team working to build a unique, world-class advertising group with a relentless focus on the customer, you&rsquo;ve come to the right place.<br>
<br>
About our team:<br>
Our team, CreativeX optimizations, is responsible for tailoring the visual experience of ads to each context in real time. To accomplish this, we are investing in latent-diffusion models, large language models (LLM), reinforced learning (RL), Computer Vision, and related methods.<br>
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Key job responsibilities<br>
We are looking for talented Applied Scientists who are adept at a variety of skills, especially with reinforcement learning and recommendations, and familiarity with LLMs, latent diffusion, or related foundational models that will accelerate our plans to dynamically optimize ad creatives on behalf of advertisers. The role will focus on developing predictive creative recommendations along with insights to improve campaign performance and creative generation process. Every member of the team is expected to build customer (advertiser) facing features, contribute to the collaborative spirit within the team, publish, patent, and bring state-of-the-art research to raise the bar within the team.</p><h2 class="jobSectionHeader"><b>
BASIC QUALIFICATIONS</b></h2><ul><li>PhD, or Master's degree and 3+ 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 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"><b>
PREFERRED QUALIFICATIONS</b></h2><ul><li>Experience using Unix/Linux</li><li>Experience in professional software development</li><li>Experience building machine learning models or developing algorithms for business application</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 II, Creative X - RAPID

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