applied scientist, agi

applied scientist, nlp/genai Jobs in New York

applied scientist, nlp/genai

associate research scientist (part-time) Jobs in New York

associate research scientist (part-time)

associate researcher ii-renal Jobs in New York

associate researcher ii-renal

clinical research coordinator Jobs in New York

clinical research coordinator

ai research scientist

DataAnnotation

<div>
 We are looking for an Energy Research Scientist to join our team to train AI models. You will measure the progress of these AI chatbots, evaluate their logic, and solve problems to improve the quality of each model.
 
 
 In this role you will need to hold an expert level of physics. Other related fields include, but are not limited to: Physics and/or Applied Mathematics.
 
 
 
 Benefits
 
 
 
 <ul>
 <li>
 This is a full-time or part-time REMOTE position
 </li>
 <li>
 You&rsquo;ll be able to choose which projects you want to work on
 </li>
 <li>
 You can work on your own schedule
 </li>
 <li>
 Projects are paid hourly starting at $40+ USD per hour, with bonuses on high-quality and high-volume work
 
 
 </li>
 </ul>
 
 Responsibilities
 
 
 
 <ul>
 <li>
 Give AI chatbots complex physics problems and evaluate their outputs
 </li>
 <li>
 Evaluate the quality produced by AI models for correctness and performance
 
 
 </li>
 </ul>
 
 Qualifications
 
 
 
 <ul>
 <li>
 Fluency in English (native or bilingual level)
 </li>
 <li>
 Detail-oriented
 </li>
 <li>
 Strong grasp of classical mechanics, E&amp;M, thermodynamics, and basic quantum concepts
 </li>
 <li>
 A current, in progress, or completed Master's and/or PhD is preferred but not required
 
 
 </li>
 </ul>
 
 Notes
 
 
 
 Payment is made via PayPal. We will never ask for any money from you. PayPal will handle any currency conversions from USD. Only applicants in the United States will be considered for this role. This is an independent contract position.
 
 
 #physics
</div>

Energy Research Scientist

Thomson Reuters

<div>Lead Applied Scientist, Document Understanding
Document understanding is a foundational intelligence layer that powers every major capability across our legal AI platform&mdash;from search and information extraction to agentic reasoning in products like Westlaw, PracticalLaw, and CoCounsel. You'll build state-of-the-art semantic chunking, document enrichment, and knowledge graph construction systems that serve as the cognitive foundation multiple product teams depend on, working across authoritative legal, tax, and accounting content and extraordinarily diverse customer data.
This is a rare opportunity to solve publishing-quality research problems with immediate production impact&mdash;your innovations will directly shape how millions of legal professionals research, analyze, and reason over complex legal documents while advancing the capabilities that enable the next generation of intelligent legal AI agents.
About the Role
As a Lead Applied Scientist, you will:
Innovate &amp; Deliver at Scale
<ul><li>Lead the design, build, test, and deployment of end-to-end AI solutions for complex document understanding tasks in the legal domain
</li><li>Direct the execution of large-scale projects including: advanced semantic chunking models for lengthy, non-uniformly structured legal documents with adjustable granularity; document enrichment systems with legal and customer-defined taxonomies; LLM-based knowledge graph construction pipelines that extract and link heterogeneous legal knowledge; and scalable synthetic data generation systems
</li><li>Serve as the technical lead and primary point of reference, ensuring full accountability for all research deliverables
</li><li>Partner with engineering to guarantee well-managed software delivery and reliability at scale across multiple product lines
</li></ul>Evaluate, Optimize &amp; Advance Capabilities
<ul><li>Design comprehensive evaluation strategies for both component-level and end-to-end quality, leveraging expert annotation and synthetic data
</li><li>Apply robust training methodologies that balance performance with latency requirements
</li><li>Lead knowledge distillation initiatives to compress large models into production-ready SLMs
</li><li>Maintain scientific and technical expertise through product deliverables, published research, and intellectual property contributions
</li><li>Inform Labs shared capabilities and research themes through novel approaches to challenging business problems
</li></ul>Drive Strategic Technical Direction
<ul><li>Independently determine appropriate architectures for complex document understanding challenges, balancing accuracy, efficiency, and scalability
</li><li>Make critical technical decisions on semantic chunking strategies, document classification approaches, LLM-based knowledge extraction methods, and multi-document reasoning architectures
</li><li>Provide input to business stakeholders, mid-to-senior level leadership, and Labs leadership on long-term AI strategy
</li><li>Develop in-depth knowledge of TR customers and data infrastructure across multiple products to shape technical roadmaps
</li></ul>Align, Communicate &amp; Lead
<ul><li>Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable, production-ready solutions
</li><li>Engage stakeholders across multiple product lines to deeply understand use case requirements, shaping objectives that align document understanding capabilities with diverse business needs including next-generation search and deep legal research
</li><li>Mentor and coach team members with varied ML/NLP abilities, building technical capability across the organization
</li></ul>About You
Required Qualifications
<ul><li>PhD in Computer Science, AI, NLP, or a related field, or a Master's degree with equivalent research/industry experience
</li><li>7+ years of hands-on experience building and deploying document understanding systems, information extraction pipelines, or knowledge graph construction using deep learning, LLMs, and NLP methods
</li><li>Proven ability to translate complex document understanding problems into innovative AI applications that balance accuracy and efficiency
</li><li>Demonstrated ability to provide technical leadership, mentor team members, and influence without formal authority in an applied research setting
</li><li>Strong programming skills (e.g., Python) and experience with modern deep learning frameworks (e.g., PyTorch, Hugging Face Transformers, DeepSpeed)
</li><li>Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS, SIGIR, or KDD
</li></ul>Technical Qualifications
<ul><li>Deep understanding of document understanding fundamentals: document layout analysis, semantic chunking approaches beyond fixed-size or paragraph-based methods, document classification handling hierarchical taxonomies, imbalanced multi-label classification, and adapting to domain-specific schemas
</li><li>Expertise in knowledge extraction and knowledge graph construction: entity recognition and linking, relation extraction, citation parsing, and building graph representations from unstructured text
</li><li>Expertise in LLM-based information extraction, few-shot and multi-task learning, post-training, and knowledge distillation
</li><li>Solid understanding of synthetic data generation techniques for NLP, including query-answer generation with verification and scalable data augmentation for training specialized models
</li><li>Solid understanding of efficiency optimization including knowledge distillation, model compression, and designing SLM-based solutions that balance performance with computational constraints
</li><li>Solid understanding of DL/ML approaches used for NLP tasks
</li><li>Experience designing annotation workflows, creating high-quality labeled datasets with clear guidelines, and developing evaluation frameworks for document understanding tasks
</li></ul>Preferred Qualifications
<ul><li>Prior work on legal document understanding, legal information extraction, knowledge representation including legal citations and legal domain concepts, or legal AI applications
</li><li>Prior work handling complex document structures common in legal documents: non-uniform formatting, nested hierarchies, cross-references, and embedded elements
</li><li>Experience building systems that perform analysis, question answering, or retrieval across large document collections
</li><li>Experience with knowledge graph frameworks and methodologies for legal or enterprise applications
</li><li>Understanding of RAG and agentic workflows for enterprise knowledge
</li><li>Experience working with AzureML or AWS SageMaker
</li></ul>#LI-LP2
What&rsquo;s in it For You?
<ul><li>Flexibility &amp; Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
</li><li>Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow&rsquo;s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
</li><li>Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
</li><li>Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
</li><li>Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
</li><li>Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
</li></ul>In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and AD&amp;D insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption &amp; Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan.
Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations.&amp;#xa;&amp;#xa;For any eligible US locations, unless otherwise noted, the base compensation range for this role is $147,000 - $273,000.&amp;#xa;&amp;#xa;This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.&amp;#xa;Base pay is positioned within the range based on several factors including an individual&rsquo;s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs.&amp;#xa;
This job posting will close 12/17/2025.
About Us
Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here .
Learn more on how to protect yourself from fraudulent job postings here .
More information about Thomson Reuters can be found on thomsonreuters.com.</div>

Lead Applied Scientist, NLP/GenAI

Amazon.com

<div><h2 class="jobSectionHeader">DESCRIPTION</h2><div>
The Artificial General Intelligence (AGI) team is looking for a highly skilled and experienced Applied Scientist, to support the development and implementation of state-of-the-art algorithms and models for supervised fine-tuning and reinforcement learning through human feedback and and complex reasoning; with a focus across text, image, and video modalities. 
 
As an Applied Scientist, you will play a critical role in supporting the development of Generative AI (Gen AI) technologies that can handle Amazon-scale use cases and have a significant impact on our customers' experiences. 
 
Key job responsibilities 
<ul><li>Collaborate with cross-functional teams of engineers, product managers, and scientists to identify and solve complex problems in Gen AI</li><li>Design and execute experiments to evaluate the performance of different algorithms and models, and iterate quickly to improve results</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>Communicate results and insights to both technical and non-technical audiences, including through presentations and written reports</li></ul></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>PhD in computer science, machine learning, engineering, or related fields</li><li>Experience or publications related to Agentic AI applications</li><li>Programming skills in Python and experience with deep learning frameworks such as Tensor Flow or PyTorch</li><li>Excellent problem-solving skills, with the ability to think creatively and critically about complex problems</li><li>Strong communication and collaboration skills, with the ability to work effectively with cross-functional teams</li><li>Experience with patents or publications at top-tier peer-reviewed conferences or journals</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. 
 
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Applied Scientist, AGI

<div><div><div>Document understanding is a foundational intelligence layer that powers every major capability across our legal AI platform&mdash;from search and information extraction to agentic reasoning in products like Westlaw, PracticalLaw , and CoCounsel . You'll build state-of-the-art semantic chunking, document enrichment, and knowledge graph construction systems that serve as the cognitive foundation multiple product teams depend on, working across authoritative legal , tax and accounting content and extraordinarily diverse customer data. This is a rare opportunity to solve publishing-quality research problems with immediate production impact&mdash;your innovations will directly shape how millions of legal professionals research, analyze, and reason over complex legal documents while advancing the capabilities that enable the next generation of intelligent legal AI agents.
About the role
</div><div>As an Applied Scientist, you will: 
</div><div><ul><li>Innovate &amp; Deliver: Design, build, test, and deploy end-to-end AI solutions for complex document understanding tasks in the legal domain. Develop advanced models for semantic chunking of lengthy, non-uniformly structured legal documents with adjustable granularity levels for different use cases. Build document enrichment systems that classify documents according to legal and customer-defined taxonomies and extract rich metadata. Create LLM-based knowledge graph construction pipelines that extract and link heterogeneous legal knowledge including citations, entities, and legal concepts across diverse legal content. Develop scalable synthetic data generation systems to support model training, simulate complex legal research queries and generate hallucination-free answers. Work in collaboration with engineering to ensure well-managed software delivery and reliability at scale.
</li></ul></div><div><ul><li>Evaluate &amp; Optimize: Develop comprehensive data and evaluation strategies for both component-level and end-to-end quality, leveraging expert human annotation and synthetic data generation. Apply robust training and evaluation methodologies that balance model performance with latency requirements, particularly for SLM-based solutions. Apply knowledge distillation techniques to compress large models into efficient SLMs suitable for production deployment.
</li></ul></div><div><ul><li>Drive Technical Decisions: Independently determine appropriate architectures for challenging document understanding problems including: semantic chunking strategies that handle diverse document formats, preserve legal document structure, and adapt to different granularity needs; document classification approaches that work across varying legal taxonomies and generalize to customer-defined schemas; LLM-based knowledge extraction methods that handle challenges like citation recognition errors and contextual references; multi-document reasoning architectures for generating synthetic multi-hop queries that reflect complex legal research patterns. Balance accuracy, efficiency, and scalability while solving real-world challenges like handling diverse document formats and content types.
</li></ul></div><div><ul><li>Align &amp; Communicate: Partner closely with Engineering and Product teams to translate complex legal document understanding challenges into scalable, production-ready solutions. Engage stakeholders across multiple product lines to deeply understand use case requirements, shaping objectives that align document understanding capabilities with diverse business needs including next -generation search and deep legal research.
</li></ul></div><div><ul><li>Advance the Field : Maintain scientific and technical expertise in one or more relevant areas as demonstrated through product deliverables, published research at top venues (e.g., ACL, EMNLP, ICLR, NeurIPS , SIGIR, KDD ) , and intellectual property. 
</li></ul></div><div>About You
</div><div><ul><li>PhD in Computer Science, AI, NLP, or a related field, or a Master's with equivalent research/industry experience
</li></ul></div><div><ul><li>3 + years of hands-on experience building and deploying document understanding systems, information extraction pipelines, or knowledge graph construction using deep learning, LLMs and NLP methods
</li></ul></div><div><ul><li>Proven ability to translate complex document understanding problems into innovative AI applications that balance accuracy and efficiency
</li></ul></div><div><ul><li>Professional experience scaling yourself and leading through others, in an applied research setting
</li></ul></div><div><ul><li>Strong programming skills (e.g., Python) and experience with modern deep learning frameworks (e.g., PyTorch , Hugging Face Transformers, DeepSpeed )
</li></ul></div><div><ul><li>Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS , SIGIR, KDD 
</li></ul></div></div><div><div>Technical Qualifications
</div><div><ul><li>Deep understanding of document understanding fundamentals: document layout analysis, semantic chunking approaches beyond fixed-size or paragraph-based methods, document classification handling hierarchical taxonomies, imbalanced multi-label classification, and adapting to domain-specific schemas
</li></ul></div><div><ul><li>Expertise in knowledge extraction and knowledge graph construction: entity recognition and linking, relation extraction, citation parsing, and building graph representations from unstructured text
</li></ul></div><div><ul><li>Expertise in LLM-based information extraction, few-shot and multi-task learning, post- training and knowledge distillation
</li></ul></div><div><ul><li>Solid understanding of synthetic data generation techniques for NLP, including query - answer generation with verification and scalable data augmentation for training specialized models
</li></ul></div><div><ul><li>Solid understanding of efficiency optimization including knowledge distillation, model compression, and designing SLM-based solutions that balance performance with computational constraints
</li></ul></div><div><ul><li>Solid understanding of DL/ML approaches used for NLP tasks
</li></ul></div><div><ul><li>Experience designing annotation workflows, creating high-quality labeled datasets with clear guidelines, and developing evaluation frameworks for document understanding tasks 
</li></ul></div><div>Preferred Qualifications
</div><div><ul><li>Prior work on legal document understanding, legal information extraction, knowledge representation including legal citations and legal domain concepts or legal AI applications
</li></ul></div><div><ul><li>Prior work handling complex document structures common in legal documents: non-uniform formatting, nested hierarchies, cross-references, and embedded elements
</li></ul></div><div><ul><li>Experience with building systems that perform analysis, question answering or retrieval across large document collections
</li></ul></div><div><ul><li>Experience with knowledge graph frameworks and methodologies for legal or enterprise applications
</li></ul></div><div><ul><li>Understanding of RAG and agentic workflows for enterprise knowledge
</li></ul></div><div><ul><li>Publications at relevant venues such as ACL, EMNLP, ICLR, NeurIPS , SIGIR, KDD
</li></ul></div><div><ul><li>Experience working with AzureML or AWS SageMaker 
 
</li></ul></div></div>#LI-LP2
What&rsquo;s in it For You?
<ul><li>Hybrid Work Model: We&rsquo;ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected.
</li><li>Flexibility &amp; Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance.
</li><li>Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow&rsquo;s challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
</li><li>Industry Competitive Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
</li><li>Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our values: Obsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together.
</li><li>Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
</li><li>Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world.
</li></ul>In the United States, Thomson Reuters offers a comprehensive benefits package to our employees. Our benefit package includes market competitive health, dental, vision, disability, and life insurance programs, as well as a competitive 401k plan with company match. In addition, Thomson Reuters offers market leading work life benefits with competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off), parental leave, sabbatical leave. These benefits meet or exceeds the requirements of paid time off in accordance with any applicable state or municipal laws. Finally, Thomson Reuters offers the following additional benefits: optional hospital, accident and sickness insurance paid 100% by the employee; optional life and AD&amp;D insurance paid 100% by the employee; Flexible Spending and Health Savings Accounts; fitness reimbursement; access to Employee Assistance Program; Group Legal Identity Theft Protection benefit paid 100% by employee; access to 529 Plan; commuter benefits; Adoption &amp; Surrogacy Assistance; Tuition Reimbursement; and access to Employee Stock Purchase Plan.
Thomson Reuters complies with local laws that require upfront disclosure of the expected pay range for a position. The base compensation range varies across locations.&amp;#xa;&amp;#xa;Eligible office location(s) for this role include one or more of the following: New York City, San Francisco, Los Angeles, and/or Irvine, CA; McLean, VA; Washington, DC. The base compensation range for the role in any of those locations is $125,000 - $232,100.&amp;#xa;&amp;#xa;This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.&amp;#xa;Base pay is positioned within the range based on several factors including an individual&rsquo;s knowledge, skills and experience with consideration given to internal equity. Base pay is one part of a comprehensive Total Reward program which also includes flexible and supportive benefits and other wellbeing programs.&amp;#xa;
About Us
Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news.
We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound exciting? Join us and help shape the industries that move society forward.
As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace.
Thomson Reuters makes reasonable accommodations for applicants with disabilities, including veterans with disabilities, and for sincerely held religious beliefs in accordance with applicable law. If you reside in the United States and require an accommodation in the recruiting process, you may contact our Human Resources Department at HR.Leave-Expert@thomsonreuters.com . Disability accommodations in the recruiting process may include things like a sign language interpreter, making interview rooms accessible, providing assistive technology, or other relevant accommodations. Please note this email is not intended for general recruitment questions and we will promptly respond to inquiries regarding accommodations. More information on requesting an accommodation here .
Learn more on how to protect yourself from fraudulent job postings here .
More information about Thomson Reuters can be found on thomsonreuters.com.</div>

Applied Scientist, NLP/GenAI

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

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

Amazon Web Services

<div><h2 class="jobSectionHeader">DESCRIPTION</h2>
Are you looking to work at the forefront of Machine Learning (ML) and Artificial Intelligence (AI)? Would you be excited to apply AI algorithms to solve real world problems with significant impact? The Amazon Web Services Professional Services (ProServe) team is seeking a skilled Senior Data Scientist to help customers implement AI/ML solutions and realize transformational business opportunities.
 
 
This is a team of scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, select and train and fine-tune the right models, define paths to navigate technical or business challenges, develop scalable solutions and applications, and launch them in production. The team provides guidance and implements best practices for applying AI responsibly and cost efficiently.
 
 
You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
 
 
We&rsquo;re looking for Data Scientists capable of using AI/ML and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
 
 
Key job responsibilities 
As an experienced Senior Data Scientist, you will be responsible for:
 
1. Lead end-to-end AI/ML and GenAI projects, from understanding business needs to data preparation, model development, solution deployment, and post-production monitoring 
2. Collaborate with AI/ML scientists, engineers, and architects to research, design, develop, and evaluate AI algorithms and build ML systems and operations (MLOps) using AWS services to address real-world challenges 
3. Interact with customers directly to understand the business challenges, deliver briefing and deep dive sessions to customers and guide them on adoption patterns and paths to production 
4. Create and deliver best practice recommendations, tutorials, blog posts, publications, sample code, and presentations tailored to technical, business, and executive stakeholders 
5. Provide customer and market feedback to product and engineering teams to help define product direction 
This is a customer-facing role with potential travel to customer sites as needed. 
 
About the team 
ABOUT AWS: 
 
Diverse Experiences
 
Amazon values diverse experiences. Even if you do not meet all of the preferred 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. 
 
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. 
 
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 and 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.<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 guiding and coaching a group of researchers 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 Python, Perl, or another scripting language</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. 
 
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $125,500/year in our lowest geographic market up to $212,800/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.</div>

Data Scientist, AWS Professional Services

Biohub

<div>
 Biohub is leading the new era of AI-powered biology to cure or prevent disease through its 501c3 medical research organization, with the support of the Chan Zuckerberg Initiative.
 
 
 The Team
 
 
 Biohub is a group of nonprofit research institutes that bring together scientists, engineers, and physicians with the goal of pursuing grand scientific challenges on 10- to 15-year time horizons. Biohub focuses on understanding underlying mechanisms of disease and developing new technologies that will lead to actionable diagnostics and effective therapies.
 
 
 Our Vision
 
 
 <ul>
 <li>
 We pursue large scientific challenges that cannot be pursued in conventional environments
 </li>
 <li>
 We enable individual investigators to pursue their riskiest and most innovative ideas
 </li>
 <li>
 The technologies developed at the Biohub facilitate research by scientists and clinicians at our home institutions and beyond
 
 
 </li>
 </ul>
 Diversity of thought, ideas, and perspectives are at the heart of Biohub and enable disruptive innovation and scholarly excellence. We are committed to cultivating an organization where all colleagues feel inspired and know their work makes an important contribution.
 
 
 The Opportunity
 
 
 The Laboratory of Immunogenomics at Biohub studies the non-coding regulatory genome to understand and address immune dysfunction in diseases like cancer, autoimmune disorders, and aging. We focus on enhancers&mdash;non-coding, highly cell&ndash;type&ndash;specific transcriptional regulatory elements&mdash;and their role in shaping immune responses. We develop and utilize genomic technologies, including bulk and single-cell nascent RNA sequencing, genome editing, immune engineering, and CRISPR-based functional screens in patient biopsies, organoid systems, and mouse models. Through computational analysis integrating machine learning and AI, we map enhancer&ndash;gene networks and identify disease-driving elements. Our goal is to advance enhancer-guided precision genomic medicine for diseases involving immune dysfunction.
 
 
 We are seeking a highly motivated
 
 Scientist
 
 to lead the development of a high-throughput adaptation of a newly established single-cell nascent RNA sequencing method (scGRO-seq) and apply it to patient biopsies and organoid models. The role involves designing, optimizing, and benchmarking cutting-edge single-cell genomics workflows, integrating them with perturbation-based assays, and generating datasets that drive transformative insights into immune regulation.
 
 
 For candidates with demonstrated technical expertise and leadership ability, this position offers the opportunity to build and
 
 lead a small team
 
 (one to two research associates) to implement the assay, conduct perturbation experiments, and oversee data generation. Once the workflow is established, this position will direct experimental execution, coordinate large-scale data acquisition, and collaborate on downstream analyses with computational biologists to deliver actionable translational insights.
 
 
 This role is ideal for a post-PhD scientist with a proven track record in single-cell biology who excels at the intersection of technological innovation, complex biology, and computational analysis. You will join a highly collaborative team working toward a shared vision. The position offers rich
 
 opportunities for professional growth
 
 &mdash;developing leadership, mentorship, and multidisciplinary expertise&mdash;equipping the candidate to thrive at the cutting-edge of single-cell immunogenomics for future academic or industry roles.
 
 
 What You'll Do
 
 
 <ul>
 <li>
 Assay development: Design, optimize, and scale high-throughput single-cell/nuclei extraction, barcoding, and library preparation workflows for scGRO-seq.
 </li>
 <li>
 Perturbation integration: Combine scGRO-seq with CRISPR-based enhancer perturbation, drug treatments, and multi-omics profiling.
 </li>
 <li>
 Molecular biology techniques: Execute advanced methods including assay design, cell manipulation, RNA/DNA isolation, PCR/qPCR, NGS library construction, high-dimensional flow cytometry, and sequencing.
 </li>
 <li>
 Translational applications: Adapt and validate protocols in patient biopsies and 3D organoid models, with emphasis on reproducibility and sensitivity.
 </li>
 <li>
 Immune cell engineering: Isolate, culture, and reprogram hematopoietic stem/progenitor cells (HSPCs) and primary immune subsets.
 </li>
 <li>
 Data integration: Partner with computational biologists to process and interpret large-scale single-cell datasets (RNA, chromatin, proteomics) using established and custom pipelines (e.g., Bowtie, STAR, Seurat, Scanpy).
 </li>
 <li>
 Collaboration &amp; dissemination: Collaborate across disciplines to investigate regulatory genomics in immune dysfunction, tumor-infiltrating immune cells, and autoimmune disease variants. Contribute to publications, preprints, conference presentations, and grant proposals.
 
 
 </li>
 </ul>
 What You'll Bring
 
 
 Essential -
 
 
 <ul>
 <li>
 2+ years of postdoctoral or equivalent post-PhD experience in academic or industry settings.
 </li>
 <li>
 PhD in Molecular Biology, Systems Biology, Genetics, Immunology, Cancer Biology, Biomedical Engineering, or related field.
 </li>
 <li>
 Proven expertise in single-cell or spatial omics technology development, ideally in RNA biology or immune engineering.
 </li>
 <li>
 Demonstrated success in genomic assay development from concept to implementation.
 </li>
 <li>
 Strong background in immune cell biology, innate and adaptive immunity, and hematopoietic stem/progenitor cell culture and reprogramming.
 </li>
 <li>
 Experience designing and executing CRISPR screens and perturbation assays (genetic or chemical/drug).
 </li>
 <li>
 Strong problem-solving skills, independence, and the ability to troubleshoot complex workflows.
 </li>
 <li>
 Excellent communication skills and proven ability to work in collaborative, multidisciplinary teams.
 
 
 </li>
 </ul>
 Nice to have -
 
 
 <ul>
 <li>
 Computational fluency in genomic data analysis; ability to work with bioinformatics pipelines for single-cell and bulk datasets.
 </li>
 <li>
 Experience with functional genomics in immune cells.
 </li>
 <li>
 Familiarity with 3D culture systems or hydrogels for immune cell studies.
 </li>
 <li>
 Experience integrating multi-modal single-cell datasets (RNA, ATAC, proteomics).
 </li>
 <li>
 Working knowledge of Linux/HPC environments and single-cell analysis tools (e.g., Seurat, Scanpy).
 
 
 </li>
 </ul>
 
 Compensation
 
 
 
 The New York City, NY base pay range for a new hire in this role is Scientist I = $120,000.00 - $165,000.000 and Scientist II = $138,000.00 - $189,000.00. New hires are typically hired into the lower portion of the range, enabling employee growth in the range over time. Actual placement in range is based on job-related skills and experience, as evaluated throughout the interview process.
 
 
 
 Benefits For The Whole You
 
 
 
 We&rsquo;re thankful to have an incredible team behind our work. To honor their commitment, we offer a wide range of benefits to support the people who make all we do possible.
 
 
 <ul>
 <li>
 Provides a generous employer match on employee 401(k) contributions to support planning for the future.
 </li>
 <li>
 Paid time off to volunteer at an organization of your choice.
 </li>
 <li>
 Funding for select family-forming benefits.
 </li>
 <li>
 Relocation support for employees who need assistance moving
 
 
 </li>
 </ul>
 If you&rsquo;re interested in a role but your previous experience doesn&rsquo;t perfectly align with each qualification in the job description, we still encourage you to apply as you may be the perfect fit for this or another role.
 
 
</div>

Scientist, Single Cell Technology Development & Translational Genomics

Explore 443+ Ai research scientist in New York this December. Find roles across top companies and apply now to boost your career.