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clinical research coordinator i Jobs in Seattle

clinical research coordinator i

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applied scientist ii, amazon connect Jobs in Seattle

applied scientist ii, amazon connect

applied scientist ii, prime video personalization and discovery science Jobs in Seattle

research scientist

Boeing

<div>Seattle, Washington
Job ID JR2026507072 Category Data Science &amp; Analytics Role Type Onsite Post Date Apr. 27, 2026<div> 
</div><div>Job Description
At Boeing, we innovate and collaborate to make the world a better place. We&rsquo;re committed to fostering an environment for every teammate that&rsquo;s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
Boeing's Global Talent, Development and Employee Experience organization has an exciting opportunity for a Senior Research Data Scientist to join the Employee Listening, Organizational Research, and Talent Assessment Team in Seattle, WA. The person in this role will lead deep dive analysis of employee survey, assessment, and workforce data, uncover meaningful organizational insights, and translate complex findings into compelling executive level narratives. This role sits at the intersection of research, analytics, strategy, and storytelling, ideal for someone who thrives on turning data into action and influencing senior leaders with clarity and confidence. You will help set the long-term research roadmap, defining measurement frameworks and success metrics, and establish standards for scientific rigor, reproducibility, practical and responsible use of AI/ML.
In this role, you will analyze large and complex datasets from surveys, assessments, HR systems, and business sources to generate actionable insights that inform organizational strategy, talent decisions, and employee experience improvements. You will lead mixed methods research, apply advanced statistical and predictive analytics, and use both structured and unstructured data to identify business trends, drivers, risks, and opportunities.
You will partner with executive leaders, HR, talent, and business teams to frame research questions, synthesize findings, and shape decisions through high impact reporting and storytelling. The ideal candidate combines strong technical expertise with the ability to simplify complex information, influence stakeholders, and help leaders understand the &ldquo;so what&rdquo; behind the data.
Position Responsibilities:<ul><li>
Lead advanced analysis of organizational survey, assessment, and workforce data to identify trends, drivers, risks, and opportunities</li><li>
Design and execute research approaches to answer complex business and organizational questions using survey, assessment, interview, and workforce data</li><li>
Translate ambiguous data into decision-ready executive syntheses, including recommendations, options, trade-offs, risks, and implementation considerations</li><li>
Develop high-impact executive reports, presentations, and dashboards that tell a compelling data story</li><li>
Partner with leaders, HR, talent, and business teams to define research questions and inform strategy</li><li>
Synthesize multiple data sources, including surveys, assessments, open-ended feedback, internal business outcome metrics, and external benchmarks</li><li>
Apply advanced statistical analysis, machine learning, and predictive modeling to surface insights and forecast outcomes</li><li>
Advance NLP methods, including sentiment analysis, topic modeling, and entity recognition, to analyze unstructured text data</li><li>
Conduct qualitative analysis, including coding, thematic analysis, and content analysis, to derive insights from narrative data</li><li>
Ensure scientific rigor, validity, and reproducibility across all research and analytics through documented methods, version-controlled code, QA checks, and peer review</li><li>
Present findings to senior stakeholders with confidence, clarity, and influence</li><li>
Improve research methodologies, reporting standards, and storytelling approaches</li><li>
Provide technical leadership, guidance, and mentoring to cross-functional partners and teammates</li><li>
Identify and implement practical AI use cases that streamline workflows, automate repetitive tasks, improve analytical efficiency, and scale research output</li><li>
Partner with other scientists to build team capability through coaching, documentation, and examples of effective day-to-day AI use</li></ul>
Basic Qualifications (Required Skills/Experience):<ul><li>
Master&rsquo;s degree or higher in a quantitative field such as Data Science, Statistics, Economics, Operations Research, Machine Learning, Engineering, Industrial Organizational Psychology, Organizational Behavior, Psychometrics, Sociology, or a related discipline</li><li>
5+ years of experience in data science, quantitative research science, or data analytics</li><li>
5+ years of experience with the following data analytics methods Machine Learning, Simulation, Statistics, Data Mining, Regression, Survival Analysis, Time series models</li><li>
5+ years of experience in data analysis algorithms (e.g. data mining, statistics, machine learning, natural language processing, text mining, visual analytics) and building Descriptive, Predictive and Prescriptive models</li><li>
5+ years of experience in database management, programming, statistical modeling and/or machine learning (SQL, R, Python, JMP, Tableau, etc.)</li><li>
Experience in Business Intelligence/data analytics tools (Microsoft Power BI, Dashboards, SQL, Tableau, etc.)</li></ul>
Preferred Qualifications (Desired Skills/Experience):<ul><li>
10+ years of industry experience</li><li>
Experience with HR systems and employee data environments</li><li>
Experience applying AI to automate, accelerate, or optimize analytics, research, or reporting workflows</li><li>
Experience with employee engagement, culture, leadership, talent, or organizational effectiveness research</li><li>
Experience applying machine learning models from ideation through monitoring and maintenance</li><li>
Capability to present highly technical information to nontechnical audiences</li><li>
Capability to influence senior leaders on strategy, trade-offs, and policy decisions using evidence-based recommendations</li><li>
Experience applying leading AI techniques and libraries to solve complex business problems and deliver measurable results</li><li>
Strong visualization skills and experience creating compelling charts, dashboards, and executive summaries</li><li>
Experience teaching, mentoring, and developing others</li></ul>
Conflict of Interest:
Successful candidates for this job must satisfy the Company's Conflict of Interest (COI) assessment process.
Drug Free Workplace:
Boeing is a Drug Free Workplace where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies.
Pay &amp; Benefits:
At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities.
The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work.
The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements.
Pay is based upon candidate experience and qualifications, as well as market and business considerations.
Summary pay range: $255,000 - $345,000 

Applications for this position will be accepted until May. 19, 2026 

Export Control Requirements:
This is not an Export Control position.
Education
Master's Degree or Equivalent Required
Relocation
Relocation assistance is not a negotiable benefit for this position.
Visa Sponsorship
Employer will not sponsor applicants for employment visa status.
Shift
This position is for 1st shift 

Equal Opportunity Employer:
Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.</div></div>
 <div><h2 class="jobSectionHeader">Your Benefits</h2>
No matter where you are in life, our benefits help prepare you for the present and the future.
<ul><li><div>Generous company match to your 401(k).</div></li>
<li><div>Industry-leading tuition assistance program pays your institution directly.</div></li>
<li><div>Fertility, adoption, and surrogacy benefits.</div></li>
<li><div>Up to $10,000 gift match when you support your favorite nonprofit organizations.</div></li></ul> 

These programs are subject to eligibility requirements and other conditions, which may differ for employees of certain subsidiaries or business units, or union-represented employees depending on bargaining agreement terms. If this information conflicts with the program documents, the latter shall control. This material is informational only.</div>

Senior Research Data Scientist

ByteDance

Location: 
Seattle
 
Team: 
Technology
 
Employment Type: 
Regular
 
Job Code: 
A162806C
 
Responsibilities
 
We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.
 
Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.
 
Team Introduction: 
We are the business owners of the AI Compute layer and DPU at ByteDance, and the creator and open-source maintainer of AIBrix, a Kubernetes-native control plane for large-scale LLM inference. We are building the next-generation AI-native computing stack—a vertically integrated system spanning hardware acceleration, distributed orchestration, and model serving—to power some of the largest AI workloads in the world.
 
Our organization—AI Compute + DPU—unifies three foundational layers:
 <ul>
<li>AI Compute & Orchestration</li>
</ul>
Planet-scale, cloud-native scheduling and serverless systems built on Kubernetes, operating across hundreds of clusters with hundreds of millions of containers and jobs daily.
 <ul>
<li>Inference Infrastructure</li>
</ul>
We support Seed business workloads (including SeedDance and other ByteDance models), as well as a wide range of open-source models. Through the open-sourcing of AIBrix, we are re-architecting LLM inference around KV cache systems, multimodal serving, advanced scheduling, and disaggregated execution, pushing the frontier of performance, cost efficiency, and latency.
 <ul>
<li>DPU & Hardware-Accelerated Systems</li>
</ul>
Next-generation software–hardware co-design across compute, networking, and storage—covering GPU virtualization, RDMA/DPDK-based networking, high-speed interconnects, and distributed storage acceleration.
 Together, we operate a globally distributed, hyperscale AI infrastructure powering products such as Doubao/Dola and CapCut, with a rapidly growing fleet of accelerators and increasingly deep integration with open-source ecosystems.
 
What Makes This Different
 This is not an incremental infrastructure team.
 
We are redefining how AI systems are built and operated: 
<ul>
<li>Re-architecting LLM inference for heterogeneous, disaggregated environments</li>
<li>Designing next-generation scheduling and caching primitives for AI workloads</li>
<li>Bridging research breakthroughs with production systems at scale</li>
<li>Building infrastructure that can self-optimize via AI (AI for systems)</li>
<li>Driving cost-efficiency at extreme scale (GPU, CPU, network, power)</li>
</ul>
This is a system-defining opportunity to work on problems that do not yet have established solutions.
 
Who We Are Looking For
 Through our Global Frontier Recruitment Program, we are selectively hiring a very small number of PhD candidates (graduating 2026–2027) who demonstrate the potential to: define technical directions, lead complex systems end-to-end, and create lasting impact in AI infrastructure.
 We are not looking for strong candidates.
 We are looking for candidates whose absence would be felt.
 
Topic Content: 
With the large-scale adoption of LLMs and AI agents, traditional cloud-native infrastructure can no longer meet the ultra-high performance and elasticity requirements of AI workloads. This topic conducts systematic research across the entire AI infrastructure stack:
 1. Network and Observability: Research intelligent fault localization and root cause analysis for large-scale AI clusters, combined with intelligent tuning of time-series databases to improve cluster stability.
 2. Storage Systems: Develop serverless high-performance elastic file systems and storage acceleration architectures specifically for AI scenarios, explore hardware-software co-optimization for DPU, and overcome AI storage performance bottlenecks.
 3. Data Center Power Scheduling: Research GPU/CPU/MEM heterogeneous collaborative scheduling technologies, build a heterogeneous power orchestration system for AI agents, and address scheduling challenges including heterogenous workloads and state dependencies.
 4. Vector Retrieval: Optimize core vector retrieval technologies for LLM-powered applications, building a cloud-native distributed vector index engine to meet ultra-large-scale vector retrieval demands with low latency and low cost.
 5. Intelligence and Agent Architecture: Explore automatic infrastructure optimization based on AI Agent workflows, build a self-evolvable business agent framework, and enable full-stack intelligent optimization through AI for Infra.
 
This topic aims to build a next-generation AI-native infrastructure to support the deployment of LLMs and AI agents, improve resource utilization, reduce costs, support elastic scaling, and drive the technological evolution of AI infrastructure.
 
Qualifications
 
Minimum Qualifications: 
<ul>
<li>Individuals who are completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline, with a focus on distributed and ML systems.</li>
<li>Proven first-author publications in top venues (e.g., OSDI, SOSP, NSDI, NeurIPS, MLSys, etc.) with clear technical contributions.</li>
<li>Strong system-building ability, with hands-on experience implementing or optimizing real systems beyond prototypes.</li>
<li>Solid understanding of compute, network architecture, and operating systems.</li>
<li>Deep expertise in at least one of the following: LLM inference / AI-ML systems, system optimization for AI (e.g., scheduling, observability, resource management, high-performance networking), or software-hardware co-design.</li>
<li>Demonstrated ownership of significant technical work (research or systems), with the ability to clearly articulate the problem defined, decisions made, and why the outcome depended on their contribution.</li>
<li>Strong programming skills and the ability to reason about complex system design.</li>
</ul>
Preferred Qualifications: 
<ul>
<li>A sustained track record of high-impact research, with evidence of influence (citations, follow-up work, or adoption in real systems).</li>
<li>Experience taking ideas from research to production, including deployment, evaluation, and iteration in real environments.</li>
<li>Deep expertise in frontier areas such as large-scale model training and inference, heterogeneous computing optimization across GPUs/DPUs/accelerators, software-hardware co-design (e.g., FPGA/ASIC) across networking/storage/distributed compute, or high-performance networking (e.g., RDMA, NCCL, DPDK/SPDK) with hands-on experience in network virtualization (OVS, SR-IOV, eBPF).</li>
<li>Proven ability to lead technical direction, not just contribute—e.g., defining a research agenda, owning a system component, or driving cross-functional decisions.</li>
<li>Contributions to widely used open-source systems or infrastructure projects.</li>
<li>Strong industry research experience or collaboration with leading labs</li>
<li>Ability to reason rigorously about system-level trade-offs (latency, throughput, cost, scalability) and translate them into practical designs.</li>
</ul>
Job Information
 
【For Pay Transparency】Compensation Description (Annually)
 
The base salary range for this position in the selected city is $202160 - $368220 annually.
 
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.
 
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).
 
The Company reserves the right to modify or change these benefits programs at any time, with or without notice.
 
For Los Angeles County (unincorporated) Candidates: 
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:
 
1. Interacting and occasionally having unsupervised contact with internal/external clients and/or colleagues;
 
2. Appropriately handling and managing confidential information including proprietary and trade secret information and access to information technology systems; and
 
3. Exercising sound judgment.
 
About Us
 
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.
 
Why Join ByteDance
 
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.
 
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.
 
Diversity & Inclusion
 
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.
 
Reasonable Accommodation
 
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

Research Scientist - AI Compute & DPU - Global Tech Research Program - 2027 Start (PhD)

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
If you are excited about applying your science and engineering skills in business problems in the space of Credit management, B2B Financial Service, and Payments, we invite you to consider this Applied Scientist opportunity within Amazon B2B Payments and Lending (ABPL). 
 
ABPL is seeking a Senior Applied Scientist who combines their scientific and technical expertise with business intuition to build flexible, performant, and global solutions for complex financial and risk problems. You will develop and deploy production models to enhance our product features &amp; processes that will delight our customers. 
 
Key job responsibilities 
As a Sr. Applied Scientist, you will design and build systems that support financial products. You will work closely with business partners, software and data engineers to build and deploy scalable solutions that deliver exceptional value for our customers. You will utilize intellectual and technical capabilities, problem solving and analytical skills, and excellent communication to deliver customer value. You will partner with product and operations management to launch new, or improve existing, financial products within Amazon. 
 
Responsibilities include: 
<ul><li>Understand business and product strategies, goals and objectives. Make recommendations for new techniques/strategies including GenAI innovations, agentic AI frameworks, and foundation models, and to improve customer experience and business outcomes</li><li>Apply advanced data mining, machine learning, and Generative AI techniques to create AI/ML capabilities and support Credit and Fraud Management
</li><li>Source, incorporate, and analyze alternative data to drive innovation, utilizing GenAI and foundation models
</li><li>Own production models (real time and batch), conduct code review and model monitoring to insist high bar of operating excellence and ensure high performant models
</li><li>Conduct research and educate business, product, marketing and product teams on the implementation of models and GenAI innovations, enabling strategic decision making through AI-powered insights and automation 
</li></ul> 
 
 
A day in the life 
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment. The benefits that generally apply to regular, full-time employees include: 1. Medical, Dental, and Vision Coverage 2. Maternity and Parental Leave Options 3. Paid Time Off (PTO) 4. 401(k) Plan. 
 
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you! At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you&rsquo;re passionate about this role and want to make an impact on a global scale, please apply!</div><h2 class="jobSectionHeader"> 
BASIC QUALIFICATIONS</h2><ul><li>Master's degree or equivalent in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science</li><li>5+ years experience in a science role, applying AI/ML to solve complex problems for large-scale applications</li><li>Demonstrated fluency with GenAI tools (e.g., LLMs, code assistants) to accelerate model development, feature engineering, and code generation workflows</li><li>Superior analytical skills. Demonstrated ability to identify and solve ambiguous problems</li><li>Demonstrated attention to detail and desire to roll up your sleeves</li><li>Demonstrated ability to operate both strategically and tactically in a high-energy, fast-paced environment. High degree of organization and ability to manage multiple, competing priorities</li><li>Excellent communication (verbal and written) and collaboration skills that enable you to earn trust at all levels</li><li>Proficiency in Python, SQL, or other programming language</li><li>Experience developing machine learning solutions with AWS</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science</li><li>10+ years of practical work applying AI/ML to solve complex problems for large-scale applications experience</li><li>Experience designing and deploying AI-native systems that leverage foundation models, agentic frameworks, and LLM-powered automation</li><li>Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment</li><li>3+ years experience in credit underwriting or related work in financial services domain</li><li>Project management experience for working on cross-functional projects</li><li>Proven achievements of developing and managing a long-term research vision and portfolio of research initiatives, with algorithms and models that have been successfully integrated in production systems</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>

Sr. Applied Scientist, Amazon B2B Payments and Lending, Credit and Fraud Science

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Do you want to join a team of innovative scientists to research and develop generative AI technology that would disrupt the industry? Do you enjoy dealing with ambiguity and working on hard problems in a fast-paced environment? 
 
Amazon Connect is a highly disruptive cloud-based contact center from AWS that enables businesses to deliver intelligent, engaging, dynamic, and personalized customer service experiences. The Agentic Customer Experience (ACX) org is responsible for weaving native-AI across the Connect application experiences delivered to end-customers, agents, and managers/supervisors. The Interactive AI Science team, serves as the cornerstone for AI innovation across Amazon Connect, functioning as the sole science team support high impact product including Amazon Q in Connect, Contact Lens and other key initiatives. 
 
As an Applied Scientist on our team, you will work closely with senior technical and business leaders from within the team and across AWS. You distill insight from huge data sets, conduct cutting edge research, foster ML models from conception to deployment. You have deep expertise in machine learning and deep learning broadly, and extensive domain knowledge in natural language processing, generative AI and LLM Agents evaluation and optimization, etc. You are comfortable with quickly prototyping and iterating your ideas to build robust ML models using technology such as PyTorch, Tensorflow and AWS Sagemaker. The ideal candidate has the ability to understand, implement, innovate on the state-of-the-art Agentic AI based systems. 
 
We have a rapidly growing customer base and an exciting charter in front of us that includes solving highly complex engineering and scientific problems. 
 
We are looking for passionate, talented, and experienced people to join us to innovate on modern contact centers in the cloud. The position represents a rare opportunity to be a part of a fast-growing business soon after launch, and help shape the technology and product as we grow. You will be playing a crucial role in developing the next generation contact center, and get the opportunity to design and deliver scalable, resilient systems while maintaining a constant customer focus. 
 
About the team 
Diverse Experiences 
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn&rsquo;t followed a traditional path, or includes alternative experiences, don&rsquo;t let it stop you from applying.
 
 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
 
<h2 class="jobSectionHeader">BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience</li><li>Experience building machine learning models or developing algorithms for business application</li><li>Experience in patents or publications at top-tier peer-reviewed conferences or journals</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 using Unix/Linux</li><li>Experience in professional software development</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, WA, Seattle - 142,800.00 - 193,200.00 USD annually</div>

Applied Scientist II, Amazon Connect

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
As part of the Agentic WorkSpaces organization, we empower millions of professional users&mdash;spanning enterprises, research institutions, and government agencies&mdash;through AWS WorkSpaces, a cloud-based desktop and application management platform. Our mission is to redefine productivity for users navigating complex legacy application environments by deploying agentic AI solutions that bridge the gap between generative AI and real-world enterprise workflows. 
 
We combine Amazon&rsquo;s deep operational expertise with a relentless focus on innovation to deliver AI experiences that are intuitive, scalable, and transformative. Where legacy systems pose unique challenges, we become the trusted partner for customers seeking to automate, optimize, and future-proof their workflows. 
 
The Senior Applied Scientist will lead the development of LLM-driven agentic systems tailored to AWS WorkSpaces environments. This role demands pioneering scientific approaches to solve unresolved problems at scale, balancing rapid iteration with rigorous evaluation. Success hinges on your ability to design, implement, and validate AI solutions that empower users to work smarter in legacy-heavy ecosystems. 
 
Key job responsibilities 
<ul><li>Architect agentic AI systems that leverage LLMs, computer vision, and computer-use techniques to interact with legacy applications within AWS WorkSpaces.</li><li>Build evaluation frameworks to quantify agent performance, reliability, and user impact in real-world, unstructured environments.</li><li>Fine-tune and deploy domain-specific LLMs for workspace use cases, ensuring efficiency, safety, and alignment with enterprise requirements.</li><li>Collaborate cross-functionally with peer teams (e.g., troubleshooting, onboarding, security) to embed AI capabilities across the WorkSpaces product suite&mdash;from strategic visioning to hands-on implementation.</li><li>Drive operational excellence by delivering high-quality, production-ready science components that meet Amazon&rsquo;s standards for robustness, reproducibility, and scalability.</li></ul> 
About the team 
Agentic WorkSpaces AI is the core science team within the Agentic WorkSpaces organization, dedicated to building LLM-driven agentic solutions that empower AWS WorkSpaces users&mdash;particularly in legacy application environments where modern AI struggles. We design, develop, and deploy intelligent agents leveraging LLMs, computer vision, and computer use to automate complex workflows. Collaborating closely with peer teams across troubleshooting, onboarding, and other critical areas, we integrate AI capabilities that enhance the entire WorkSpaces experience. Our work balances rapid innovation with rigorous evaluation and ethical alignment, delivering scalable, enterprise-ready solutions for millions of users worldwide.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>5+ 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 working with cross-functional teams across business development, marketing, operations, product development, legal, etc.</li><li>Expertise in computer vision or computer-use automation (e.g., UI interaction, screen understanding) to tackle unique legacy system challenges.</li><li>Experience fine-tuning LLMs for domain-specific applications, optimizing for efficiency, safety, and enterprise requirements.</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, Agentic WorkSpaces AI

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Prime Video is a first-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. Prime members can customize their viewing experience and find their favorite movies, series, documentaries, and live sports &ndash; including Amazon MGM Studios-produced series and movies; licensed fan favorites; and programming from Prime Video add-on subscriptions such as Apple TV+, Max, Crunchyroll and MGM+. All customers, regardless of whether they have a Prime membership or not, can rent or buy titles via the Prime Video Store, and can enjoy even more content for free with ads. 
 
Are you interested in shaping the future of entertainment? Prime Video's technology teams are creating best-in-class digital video experience. 
 
As a Prime Video technologist, you&rsquo;ll have end-to-end ownership of the product, user experience, design, and technology required to deliver state-of-the-art experiences for our customers. You&rsquo;ll get to work on projects that are fast-paced, challenging, and varied. You&rsquo;ll also be able to experiment with new possibilities, take risks, and collaborate with remarkable people. 
 
We&rsquo;ll look for you to bring your diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. With global opportunities for talented technologists, you can decide where a career Prime Video Tech takes you! 
 
We are looking for a self-motivated, passionate and resourceful Applied Scientist to bring diverse perspectives, ideas, and skill-sets to make Prime Video even better for our customers. You will spend your time as a hands-on machine learning practitioner and a research leader. You will play a key role on the team, building and guiding machine learning models from the ground up. At the end of the day, you will have the reward of seeing your contributions benefit millions of Amazon.com customers worldwide. 
 
Key job responsibilities 
<ul><li>Develop AI solutions for various Prime Video Recommendation and Personalization systems using Deep learning, GenAI, Reinforcement Learning, and optimization methods;</li><li>Work closely with engineers and product managers to design, implement and launch AI solutions end-to-end;</li><li>Design and conduct offline and online (A/B) experiments to evaluate proposed solutions based on in-depth data analyses;</li><li>Effectively communicate technical and non-technical ideas with teammates and stakeholders;</li><li>Stay up-to-date with advancements and the latest modeling techniques in the field;</li><li>Publish your research findings in top conferences and journals.</li></ul> 
A day in the life 
We're using advanced approaches such as foundation models to connect information about our videos and customers from a variety of information sources, acquiring and processing data sets on a scale that only a few companies in the world can match. This will enable us to recommend titles effectively, even when we don't have a large behavioral signal (to tackle the cold-start title problem). It will also allow us to find our customer's niche interests, helping them discover groups of titles that they didn't even know existed. We are looking for creative &amp; customer obsessed machine learning scientists who can apply the latest research, state of the art algorithms and ML to build highly scalable page personalization solutions. You'll be a research leader in the space and a hands-on ML practitioner, guiding and collaborating with talented teams of engineers and scientists and senior leaders in the Prime Video organization. You will also have the opportunity to publish your research at internal and external conferences.
 
 
About the team 
Prime Video Recommendation Science team owns science solution to power recommendation and personalization experience on various Prime Video surfaces and devices. We work closely with the engineering teams to launch our solutions in production.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>PhD, or Master's degree and 6+ years of applied research experience</li><li>5+ years of building machine learning models for business application experience</li><li>Experience programming in Java, C++, Python or related language</li><li>Experience with neural deep learning methods and machine learning</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.</li><li>Experience with large scale distributed systems such as Hadoop, Spark etc.</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Sunnyvale - 192,200.00 - 260,000.00 USD annually 
USA, NY, New York - 183,800.00 - 248,700.00 USD annually 
USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually</div>

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

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
Amazon Quick Suite is an enterprise AI platform that transforms how organizations work with their data and knowledge. Combining generative AI-powered search, deep research capabilities, intelligent agents and automations, and comprehensive business intelligence, Quick Suite serves tens of thousands of users. Our platform processes thousands of queries monthly, helping teams make faster, data-driven decisions while maintaining enterprise-grade security and governance. From natural language interactions with complex datasets to automated workflows and custom AI agents, Quick Suite is redefining workplace productivity at unprecedented scale. 
 
We are seeking a Data Scientist II to join our Quick Data team, focusing on evaluation and benchmarking data development for Quick Suite features, with particular emphasis on Research and other generative AI capabilities. Our mission is to engineer high-quality datasets that are essential to the success of Amazon Quick Suite. From human evaluations and Responsible AI safeguards to Retrieval-Augmented Generation and beyond, our work ensures that Generative AI is enterprise-ready, safe, and effective for users at scale. 
As part of our diverse team&mdash;including data scientists, engineers, language engineers, linguists, and program managers&mdash;you will collaborate closely with science, engineering, and product teams. We are driven by customer obsession and a commitment to excellence.
 
 
Key job responsibilities 
In this role, you will leverage data-centric AI principles to assess the impact of data on model performance and the broader machine learning pipeline. You will apply Generative AI techniques to evaluate how well our data represents human language and conduct experiments to measure downstream interactions. 
Specific responsibilities include: 
<ul><li>Design and develop comprehensive evaluation and benchmarking datasets for Quick Suite AI-powered features</li><li>Leverage LLMs for synthetic data corpora generation; data evaluation and quality assessment using LLM-as-a-judge settings</li><li>Create ground truth datasets with high-quality question-answer pairs across diverse domains and use cases</li><li>Lead human annotation initiatives and model evaluation audits to ensure data quality and relevance</li><li>Develop and refine annotation guidelines and quality frameworks for evaluation tasks</li><li>Conduct statistical analysis to measure model performance, identify failure patterns, and guide improvement strategies</li><li>Collaborate with ML scientists and engineers to translate evaluation insights into actionable product improvements</li><li>Build scalable data pipelines and tools to support continuous evaluation and benchmarking efforts</li><li>Contribute to Responsible AI initiatives by developing safety and fairness evaluation datasets</li></ul> 
About the team 
 
Why AWS? 
Amazon Web Services (AWS) is the world&rsquo;s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating &mdash; that&rsquo;s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. 
 
Inclusive Team Culture 
Here at AWS, it&rsquo;s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness. 
 
Mentorship &amp; Career Growth 
We&rsquo;re continuously raising our performance bar as we strive to become Earth&rsquo;s Best Employer. That&rsquo;s why you&rsquo;ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. 
 
Work/Life Balance 
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there&rsquo;s nothing we can&rsquo;t achieve in the cloud. 
 
Hybrid Work 
We value innovation and recognize this sometimes requires uninterrupted time to focus on a build. We also value in-person collaboration and time spent face-to-face. Our team affords employees options to work in the office every day or in a flexible, hybrid work model near one of our U.S. Amazon offices.</div><h2 class="jobSectionHeader">
BASIC QUALIFICATIONS</h2><ul><li>2+ years of data scientist experience</li><li>3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience</li><li>3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience</li><li>1+ years of working with or evaluating AI systems experience</li><li>1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience</li><li>Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Experience applying theoretical models in an applied environment</li></ul><h2 class="jobSectionHeader">
PREFERRED QUALIFICATIONS</h2><ul><li>Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)</li><li>Knowledge of machine learning concepts and their application to reasoning and problem-solving</li><li>Experience in a ML or data scientist role with a large technology company</li><li>Experience in defining and creating benchmarks for assessing GenAI model performance</li><li>Experience working on multi-team, cross-disciplinary projects</li><li>Experience applying quantitative analysis to solve business problems and making data-driven business decisions</li><li>Experience effectively communicating complex concepts through written and verbal communication</li></ul> 
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. 
 
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company&rsquo;s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 
 
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you&rsquo;re applying in isn&rsquo;t listed, please contact your Recruiting Partner. 
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life &amp; AD&amp;D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits. 
USA, CA, Santa Clara - 157,300.00 - 212,800.00 USD annually 
USA, NY, New York - 153,400.00 - 207,500.00 USD annually 
USA, WA, Seattle - 136,000.00 - 184,000.00 USD annually</div>

Data Scientist, AWS Quick Data

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