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

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Revolutionize the Future of AI at the Frontier of Applied Science 
 
Are you a brilliant mind seeking to push the boundaries of what's possible with artificial intelligence? Join our elite team of researchers and engineers at the forefront of applied science, where we're harnessing the latest advancements in natural language processing, deep learning, and generative AI to reshape industries and unlock new realms of innovation. 
 
As an Applied Science Intern, you'll have the unique opportunity to work alongside world-renowned experts, gaining invaluable hands-on experience with cutting-edge technologies such as large language models, transformers, and neural networks. You'll dive deep into complex challenges, fine-tuning state-of-the-art models, developing novel algorithms for named entity recognition, and exploring the vast potential of generative AI. 
 
This internship is not just about executing tasks &ndash; it's about being a driving force behind groundbreaking discoveries. You'll collaborate with cross-functional teams, leveraging your expertise in statistics, recommender systems, and question answering to tackle real-world problems and deliver impactful solutions. 
 
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 
 
Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. 
 
Amazon has positions available for LLM &amp; GenAI Applied Science Internships in, but not limited to, Bellevue, WA; Boston, MA; Cambridge, MA; New York, NY; Santa Clara, CA; Seattle, WA; Sunnyvale, CA; Pittsburgh, PA. 
 
Key job responsibilities 
We are particularly interested in candidates with expertise in: LLMs, NLP/NLU, Gen AI, Transformers, Fine-Tuning, Recommendation Systems, Deep Learning, NER, Statistics, Neural Networks, Question Answering. 
 
In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of LLMs and GenAI. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on recommendation systems, question answering, deep learning and generative AI. 
 
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. 
 
A day in the life 
<ul><li>Collaborate with cross-functional teams to tackle complex challenges in natural language processing, computer vision, and generative AI.</li><li>Fine-tune state-of-the-art models and develop novel algorithms to push the boundaries of what's possible.</li><li>Explore the vast potential of generative AI and its applications across industries.</li><li>Attend cutting-edge research seminars and engage in thought-provoking discussions with industry luminaries.</li><li>Leverage state-of-the-art computing infrastructure and access to the latest research papers to fuel your innovation.</li><li>Present your groundbreaking work and insights to the team, fostering a culture of knowledge-sharing and continuous learning.</li></ul></div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>Are enrolled in a PhD</li><li>Can relocate to where the internship is based</li><li>Experience programming in Java, C++, Python or related language</li><li>Must be available for full-time (40 hours per week) internship for the whole duration of the internship</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>Experience in building models for business application</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 starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location. Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching. Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits. 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

2026 Fall Applied Science Internship - Gen AI & Large Language Models - United States, PhD Student Science Recruiting

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Unlock the Future with Amazon Science! 
 
Calling all visionary minds passionate about the transformative power of machine learning! Amazon is seeking boundary-pushing graduate student scientists who can turn revolutionary theory into awe-inspiring reality. Join our team of visionary scientists and embark on a journey to revolutionize the field by harnessing the power of cutting-edge techniques in bayesian optimization, time series, multi-armed bandits and more.
 
 
At Amazon, we don't just talk about innovation &ndash; we live and breathe it. You'll conducting research into the theory and application of deep reinforcement learning. You will work on some of the most difficult problems in the industry with some of the best product managers, scientists, and software engineers in the industry. You will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. 
 
Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment where bold ideas are celebrated. 
 
Join us at the forefront of applied science, where your contributions will shape the future of AI and propel humanity forward. Seize this extraordinary opportunity to learn, grow, and leave an indelible mark on the world of technology. 
 
Amazon has positions available for Machine Learning Applied Science Internships in, but not limited to Arlington, VA; Bellevue, WA; Boston, MA; New York, NY; Palo Alto, CA; San Diego, CA; Santa Clara, CA; Seattle, WA. 
 
Key job responsibilities 
We are particularly interested in candidates with expertise in: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling
 
 
In this role, you will work alongside global experts to develop and implement novel, scalable algorithms and modeling techniques that advance the state-of-the-art in areas at the intersection of Reinforcement Learning and Optimization within Machine Learning. You will tackle challenging, groundbreaking research problems on production-scale data, with a focus on developing novel RL algorithms and applying them to complex, real-world challenges. 
 
The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment. 
 
A day in the life 
<ul><li>Develop scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.</li><li>Design, development and evaluation of highly innovative ML models for solving complex business problems.</li><li>Research and apply the latest ML techniques and best practices from both academia and industry.</li><li>Think about customers and how to improve the customer delivery experience.</li><li>Use and analytical techniques to create scalable solutions for business problems.
</li></ul></div><h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>Are enrolled in a PhD</li><li>Can relocate to where the internship is based</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling</li><li>Experience with one or more of the following: Optimization, Programming/Scripting Languages, Statistics, Reinforcement Learning, Causal Inference, Large Language Models, Time Series, Graph Modeling, Supervised/Unsupervised Learning, Deep Learning, Predictive Modeling</li><li>Must be available for full-time (40 hours per week) internship for the whole duration of the internship</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Have publications at top-tier peer-reviewed conferences or journals</li><li>Experience in state-of-the-art deep learning models architecture design and deep learning training and optimization and model pruning</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 starting pay for this position is listed below. Final starting pay will be based on factors including experience, qualifications, and location. Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching. Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits. 
USA, OR, Corvallis - 142,800.00 - 193,200.00 USD annually 
USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually 
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

2026 Fall Applied Science Internship - Reinforcement Learning & Optimization (Machine Learning) - United States, PhD Student Science Recruiting

<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

<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

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

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon is building a world class advertising business and delivering a collection of self-service performance advertising products that drive discovery and sales of merchandise. Our products are strategically important to our retail and marketplace businesses, driving long-term growth. We deliver billions of ad impressions and millions of clicks daily and are breaking fresh ground to create world-class products. We are a highly motivated, collaborative group with an entrepreneurial spirit and bias for action. With a broad mandate to experiment and innovate with a seemingly endless range of new ideas and opportunities. 
 
Key job responsibilities 
We are looking for an software dev engineer for the Conversational Ad Experiences (CAX) team within Sponsored Products and Brands (SPB). SPB helps merchants, retail vendors, and brand owners grow incremental sales of their products on Amazon through native product advertising. The CAX team focuses on sponsored conversational shopping experiences powered by large language models (LLMs). The team is working on multiple 'industry first' projects which are ambiguous and challenging, but they offer the opportunity to have a significant impact on both our shoppers and business.
 
 
As an engineer on the team, you will: 
<ul><li>Drive major product and engineering initiatives, build large-scale, low-latency distributed systems, build ML infrastructure and data processing pipelines.
</li><li>Partner with our science team to implement LLM models in production, and also contribute to LLMOps.
</li><li>Design, build, and operate key pieces of customer facing functionality impacting hundreds of millions of Amazon shoppers worldwide.</li></ul> 
About the team 
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading 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</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>3+ years of non-internship professional software development experience</li><li>2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience</li><li>Experience programming with at least one software programming language</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience</li><li>Bachelor's degree in computer science or equivalent</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 - 158,100.00 - 213,800.00 USD annually 
USA, WA, SEATTLE - 143,700.00 - 194,400.00 USD annually</div>

Software Development Engineer, Conversational Ads Experience

Starbucks

<div>Now Brewing &ndash; director of data science &ndash; Global Supply Chain Analytics! #tobeapartner
From the beginning, Starbucks set out to be a different kind of company. One that not only 
celebrated coffee and the rich tradition, but that also brought a feeling of connection. We are known for developing extraordinary leaders who share this passion and are guided by their service to others.
The Director of Supply Chain Data Science will lead the strategy, development, and deployment of advanced analytics and machine learning solutions across Starbucks&rsquo; global supply chain. This role is responsible for managing and scaling high performing teams of data scientists and data science people managers, while partnering closely with Supply Chain, Technology, Retail, and Finance leaders to deliver measurable business impact.
This leader will drive innovation across demand forecasting, network design and optimization, inventory and assortment optimization, and last mile logistics, leveraging modern algorithmic techniques and cloud native data platforms. The ideal candidate combines strong technical depth, proven people leadership, and the ability to translate complex models into clear business outcomes at scale. 
As a director of data science &ndash; Global Supply Chain, you will&hellip;
People &amp; Organizational Leadership<ul><li>
Lead, mentor, and develop multidisciplinary teams of data scientists at all levels, including senior individual contributors and people managers</li><li>
Build a strong talent pipeline through hiring, coaching, career development, and succession planning</li><li>
Foster a culture of scientific rigor, innovation, collaboration, and operational excellence</li><li>
Set clear technical and delivery standards for experimentation, production ML, and model governance</li></ul> 
Supply Chain Analytics &amp; Modeling<ul><li>
Own the data science vision and roadmap for supply chain optimization</li><li>
Lead development of demand forecasting systems (short term, mid term, and long term) incorporating promotions, seasonality, new product introductions, and external signals</li><li>
Drive network optimization initiatives including distribution centers, and transportation flows</li><li>
Build and deploy last mile logistics optimization models to improve service levels, cost, and sustainability</li><li>
Develop advanced assortment and inventory optimization models balancing customer demand, store constraints, freshness, and waste reduction</li></ul>
Advanced Analytics &amp; Algorithms<ul><li>
Apply modern machine learning, optimization, and statistical techniques, including (but not limited to):<ul><li>
Forecasting (hierarchical, probabilistic, deep learning&ndash;based)</li><li>
Operations research and mathematical optimization (linear, integer, stochastic, simulation based)</li><li>
Causal inference, experimentation, and scenario analysis</li></ul></li><li>
Ensure solutions scale across thousands of stores</li></ul>
Technology &amp; MLOps<ul><li>
Guide teams in building production grade ML systems using modern, cloud native tech stacks</li><li>
Partner with Engineering and Platform teams to ensure robust data pipelines, feature stores, model deployment, monitoring, and retraining</li><li>
Champion best practices in MLOps, model explainability, reliability, and responsible AI</li></ul>
Business Partnership &amp; Impact<ul><li>
Serve as a trusted thought partner to senior Supply Chain and Operations leadership</li><li>
Translate ambiguous business problems into well defined analytical solutions with clear KPIs and ROI</li><li>
Communicate insights and recommendations effectively to executive stakeholders, influencing strategic decisions</li><li>
Drive adoption and change management to ensure models are embedded into operational workflows</li></ul> 


We&rsquo;d love to hear from people with:<ul><li>
12+ years of experience in data science, advanced analytics, or applied machine learning, with significant focus on supply chain, logistics, or operations</li><li>
5+ years of experience managing managers and large, complex data science organizations</li><li>
Deep expertise in demand forecasting, optimization, and applied machine learning at scale</li><li>
Strong foundation in statistics, operations research, computer science, or a related quantitative field</li><li>
Hands on experience with modern data and ML ecosystems (e.g., Python, SQL, cloud platforms, distributed computing)</li><li>
Proven track record of delivering measurable business impact through advanced analytics</li><li>
Excellent executive communication and stakeholder management skills</li></ul>
Preferred Skills:<ul><li>
Experience in retail, CPG, QSR, or global consumer supply chains</li><li>
Familiarity with sustainability, waste reduction, and responsible sourcing analytics</li><li>
Advanced degree (MS or PhD) in a quantitative discipline</li><li>
Experience scaling ML systems across thousands of physical locations</li></ul>
As a Starbucks partner, you (and your family) will have access to medical, dental, vision, basic and supplemental life insurance, and other voluntary insurance benefits. Partners have access to short-term and long-term disability, paid parental leave, family expansion reimbursement, paid vacation from date of hire*, sick time (accrued at 1 hour for every 25 hours worked), eight paid holidays, and two personal days per year. Starbucks also offers eligible partners participation in a 401(k) retirement plan with employer match, a discounted company stock program (S.I.P.), Starbucks equity program (Bean Stock), incentivized emergency savings, and financial well-being tools. Additionally, Starbucks offers 100% upfront tuition coverage for a first-time bachelor&rsquo;s degree through Arizona State University&rsquo;s online program via the Starbucks College Achievement Plan, student loan management resources, and access to other educational opportunities. You will also have access to backup care and DACA reimbursement. Starbucks will comply with any applicable state and local laws regarding employee leave benefits, including, but not limited to providing time off pursuant to the Colorado Healthy Families and Workplaces Act, and in accordance with its plans and policies. This list is subject to change depending on collective bargaining in locations where partners have a certified bargaining representative. For additional information regarding partner perks and more detailed information about benefits, go to starbucksbenefits.com.<ul><li>If you are working in CA, CO, IL, LA, ME, MA, NE, ND or RI, you will accrue vacation up to a maximum of 120 hours (190 in CA) for roles below director and 200 hours (316 in CA) for roles at director or above. For roles in other states, you will be granted vacation time starting at 120 hours annually for roles below director and 200 hours annually for roles director and above.</li></ul>
The actual base pay offered to the successful candidate will be based on multiple factors, including but not limited to job-related knowledge/skills, experience, geographical location, and internal equity. At Starbucks, it is not typical for an individual to be hired at the high end of the range for their role, and compensation decisions are dependent upon the facts and circumstances of each position and candidate.
We believe we do our best work when we're together, which is why we're onsite four days a week.
Join us and inspire with every cup. Apply today!
Starbucks Coffee Company is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, or protected veteran status, or any other characteristic protected by law. 
Qualified applicants with criminal histories will be considered for employment in a manner consistent with all federal, state and local ordinances. 
 
Starbucks Coffee Company is committed to offering reasonable accommodations to job applicants with disabilities. If you need assistance or an accommodation due to a disability, please contact us at applicantaccommodation@starbucks.com or 1(888) 611-2258.</div>

director, data science- Global Supply Chain Analytics

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