Applied Scientist

Thomson Reuters is seeking an Applied Scientist to work at the forefront of applied research in AI and machine learning. The role involves developing and implementing solutions to business problems in legal, tax, and regulatory domains, while collaborating with product and engineering teams to create impactful results.

Responsibilities

• Develop and implement machine learning and AI solutions to address business problems across Thomson Reuters' legal, tax, and regulatory domains
• Design experiments
• Build models
• Translate research into production-ready features
• Collaborate with product and engineering teams to deliver measurable impact for customers

Skills

• PhD or Master's degree in Computer Science, Machine Learning, or a related field
• 1-2 years of hands-on experience building systems using modern techniques in information retrieval, NLP, machine learning, or generative AI (examples include deep learning, transformer architectures, hybrid search, dense retrieval, vector databases, or agentic systems)
• Strong programming skills in Python and familiarity with a modern ML framework (PyTorch, JAX, DeepSpeed, or similar)
• Experience working with shared codebases and version control systems
• Familiarity with cloud development environments (AWS, Azure, or GCP)
• Strong communication and problem-solving skills, with the ability to work effectively across functions
• Experience implementing and evaluating solutions with large language models and LLM evaluation frameworks (e.g., OpenAI Evals, HELM, LM Harness, or custom tools)
• Experience with retrieval-augmented generation (RAG), tool-using agents, and agentic frameworks
• Publications or preprints in relevant venues (NeurIPS, ACL, EMNLP, ICLR, SIGIR)
• Experience with production code and MLOps practices

Benefits

• Hybrid Work Model: We’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.
• 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.
• 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.
• 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.
• 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.
• Market competitive health, dental, vision, disability, and life insurance programs
• Competitive 401k plan with company match
• Competitive vacation, sick and safe paid time off, paid holidays (including two company mental health days off)
• Parental leave
• Sabbatical leave
• 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
• Access to Employee Stock Purchase Plan

Company Overview

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