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About This Role
Lead Applied Scientist, Search \& Information Retrieval
About the Role
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This role sits within the applied science function. You will own the design, development, and production deployment of large\-scale search and information retrieval systems that power Westlaw, Practical Law, CoCounsel, and next\-generation Thomson Reuters search experiences. The problems are real, the scale is large, and the expectation is shipped, reliable, measurable impact.
You will work across retrieval architectures, indexing pipelines, ranking and re\-ranking systems, semantic retrieval, hybrid search, and retrieval optimization for complex legal, tax, and accounting content. Multiple product teams depend on what this function delivers.
About You
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You hold a PhD in Computer Science, Information Retrieval, Machine Learning, NLP, or a related field, with 8\+ years of post\-degree industry experience building and deploying search and retrieval systems at scale. You have hands\-on depth across indexing, retrieval, ranking, relevance evaluation, and production deployment.
You publish, you mentor, and you measure success by what ships and performs in production. You understand search beyond simply consuming vector databases or retrieval APIs. You have built, optimized, and evaluated search systems that solve real user problems.
What You'll Do
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- Design and deploy search architectures supporting large\-scale legal, tax, and enterprise content collections
- Build and optimize ingestion pipelines that analyze, enrich, and prepare documents for retrieval
- Develop ranking and re\-ranking systems using both traditional IR techniques and modern LLM\-based approaches
- Improve retrieval quality through semantic retrieval, hybrid retrieval, query understanding, and relevance optimization
- Design evaluation frameworks for retrieval performance, relevance, ranking quality, and end\-user outcomes
- Lead technical decisions around indexing strategies, retrieval architectures, ranking models, and search infrastructure
- Partner with engineering teams to deliver scalable, reliable, and performant search services
- Contribute to the development of self\-service search platform capabilities used by internal product teams
- Provide technical input to senior leadership on search, retrieval, and AI strategy
- Mentor applied scientists and machine learning practitioners across the organization
Required Qualifications
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- PhD in Computer Science, Information Retrieval, AI, Machine Learning, NLP, or a related field preferred
- 8\+ years of industry experience building production search, information retrieval, ranking, or recommendation systems
- Publications at SIGIR, ACL, EMNLP, NeurIPS, ICLR, KDD, WWW, or equivalent venues
- Strong production Python skills and experience with PyTorch, Hugging Face Transformers, and distributed model development
### Hands\-on production depth required in:
- Search engine architecture, indexing systems, and ingestion pipelines
- Ranking and re\-ranking systems rather than solely consuming search technologies
- Information retrieval, semantic retrieval, hybrid retrieval, and vector search architectures
- Query understanding, relevance optimization, and search evaluation methodologies
- Retrieval systems supporting large collections of text\-rich content
- LLM\-enhanced retrieval, RAG architectures, and retrieval optimization
- End\-to\-end measurement and evaluation of search quality and user outcomes
Preferred Qualifications
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- Experience with legal, regulatory, tax, scientific, or other text\-heavy domains
- Building retrieval systems over large enterprise knowledge repositories
- Experience with Elasticsearch, OpenSearch, Solr, Vespa, or similar search technologies
- API platform development and self\-service search platforms
- Agentic AI systems that incorporate retrieval capabilities
- AzureML or AWS SageMaker
- Experience building systems that combine search, retrieval, and document understanding capabilities
\#LI\-SM2
This posting is for proactive recruitment purposes and may be used to fill current openings or future vacancies within our organization.
What’s in it For You?
- Flexibility \& 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.
- Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’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.
- 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.
- 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.
- 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.
- 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.
Our use of AI within the recruitment process Thomson Reuters utilizes Artificial Intelligence (AI) to support parts of our global recruitment process. Unless you opt\-out, our AI system will assess the information provided by you and compare it to the requirements listed for the role, and present the result to our recruitment personnel for further review. The AI system acts as a supporting tool, but there is always a human making the decision if you will be considered for the role.
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\&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 \& 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.\&\#xa;\&\#xa;For any eligible US locations, unless otherwise noted, the base compensation range for this role is $147,600 USD \- $274,200 USD.\&\#xa;For Ontario, Canada, the base compensation range for this role is $140,000 CAD \- $175,000 CAD.\&\#xa;\&\#xa;Base pay is positioned within the range based on several factors including an individual’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.\&\#xa;This role may also be eligible for an Annual Bonus based on a combination of enterprise and individual performance.\&\#xa;
This job posting will close 10/31/2026\.
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
Salary Context
This $140K-$274K range is above the 75th percentile for Research Scientist roles in our dataset (median: $183K across 83 roles with salary data).
Role Details
About This Role
Research Scientists push the boundaries of what AI can do. They design experiments, develop novel architectures, publish papers, and translate research breakthroughs into production capabilities. This is where the fundamental advances happen, from attention mechanisms to diffusion models to reasoning chains.
The work is intellectually demanding and often ambiguous. You might spend months on an approach that doesn't pan out. The best research scientists combine deep mathematical intuition with engineering pragmatism. They know when to go deep on theory and when to run experiments. They read papers voraciously and can spot incremental contributions from genuine breakthroughs.
Across the 3,708 AI roles we're tracking, Research Scientist positions make up 3% of the market. At Thomson Reuters, this role fits into their broader AI and engineering organization.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
What the Work Looks Like
A typical week includes: reading and discussing recent papers with your team, designing and running experiments on multi-GPU clusters, analyzing results and iterating on hypotheses, writing up findings for internal review or publication, and collaborating with engineering teams to productionize promising results. The ratio of thinking to coding is higher than in engineering roles.
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
Skills Required
PhD strongly preferred for most roles. Deep expertise in a specific area (NLP, computer vision, reinforcement learning, multimodal) is expected. PyTorch is the standard. Publication track record matters. Strong mathematical foundations in linear algebra, probability, optimization, and information theory are assumed.
Beyond the fundamentals, companies value experience with large-scale distributed training, novel architecture design, and the ability to bridge theory and practice. Understanding of current frontier topics (reasoning, multimodal, long-context, alignment) is essential. Code quality matters more than many researchers expect. Labs want researchers who can implement their ideas cleanly.
Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
Compensation Benchmarks
Research Scientist roles pay a median of $222,200 based on 197 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($207K) sits 7% below the category median. Disclosed range: $140K to $274K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Thomson Reuters AI Hiring
Thomson Reuters has 5 open AI roles right now. They're hiring across AI/ML Engineer, Research Scientist. Positions span Eagan, MN, US, New York, NY, US. Compensation range: $172K - $424K.
Location Context
AI roles in New York pay a median of $220,000 across 1,045 tracked positions.
Career Path
Common paths into Research Scientist roles include PhD Student, Research Engineer, Postdoc.
From here, career progression typically leads toward Research Lead, Distinguished Scientist, VP of Research.
The PhD is the entry point for most paths. Choose your advisor and research area carefully since they'll define your first industry position. Publish consistently, contribute to open-source projects in your area, and build relationships at conferences. Industry research offers better compensation and compute resources than academia, but the pressure to show product impact is real.
What to Expect in Interviews
Research interviews are multi-stage: a research talk (present your best paper), technical deep-dives on your methodology, and often a 'research proposal' exercise where you design an experiment to test a hypothesis. Coding rounds test implementation ability alongside theoretical knowledge. Be prepared to implement a paper from scratch and discuss the design choices the authors made. Strong candidates can critique papers constructively and identify gaps in experimental methodology.
When evaluating opportunities: Strong research postings specify the research area, mention the team you'd join, and describe the problems they're working on. They often list recent publications from the team. Vague 'AI research' postings without specifics usually mean the company wants to sound impressive but doesn't have a real research agenda.
AI Hiring Overview
The AI job market has 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 roles).
Research Scientist roles are concentrated at major AI labs (OpenAI, Anthropic, Google DeepMind, Meta FAIR) and well-funded AI startups. The competition is intense. PhD is effectively required for most positions, and publication track record matters. Compensation is among the highest in AI, reflecting both the scarcity of talent and the strategic importance of research breakthroughs.
The AI Job Market Today
The AI job market spans 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (102) are outnumbered by mid-level (1,705) and senior (1,469) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $300,000 median, while Prompt Engineer roles sit at $140,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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