Lead Applied Scientist

Thomson Reuters

Lead Applied Scientist advancing NLP, information retrieval, and GenAI for Thomson Reuters’ legal technology products. Leading applied research from proof of concept through production.

Posted 9/2/2026full-timeRemote • 🇨🇦 CanadaSenior💰 CA$140,000 - CA$175,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in leading applied research teams to develop and deliver AI solutions, particularly in Natural Language Processing (NLP) and Information Retrieval (IR). Proficient in stakeholder engagement, mentoring, and leveraging state-of-the-art technologies to drive innovation and customer value.

Highest-signal resume keywords

PhD In Relevant Discipline7+ Years Experience Building NLP/IR SystemsProficiency In Python, Git, AWS, And AzureExperience With Generative AI TechnologiesSolid Understanding Of Classic And Deep Learning Techniques

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Natural Language ProcessingInformation RetrievalMachine LearningGenerative AIModel TrainingEvaluation DesignData CurationPrompt EngineeringTransformer-Based ModelsAutoEval Methods

Soft Skills

Outstanding Communication SkillsProblem-Solving SkillsAnalytical SkillsMentoringCollaboration

Tools & Technologies

PydanticAILangGraphAutoGenSemantic KernelAgile Development PracticesLightweight UIsRemote Model DevelopmentRapid Prototyping

Certifications & Qualifications

Law Degree (J.D.)Paralegal Experience

Industry Keywords

Legal AI SystemsComplianceRegulatory DomainsPublications In ACL, EMNLP, NAACL, NeurIPSMLOps

Tech Stack

Tools & technologies

AWSAzurePython

About the role

Key responsibilities & impact

Lead an applied research team throughout the full product development life cycle from ideation and proof of concept through production scaling and feedback-driven iteration
Be fully accountable for research deliverables across projects
Lead and drive stakeholder engagement with Product, Engineering, subject-matter experts, and Design
Develop in-depth knowledge of customer problems and data
Maintain scientific and technical expertise through product deliverables, published research, and intellectual property
Identify state-of-the-art technology relevant to Thomson Reuters products and leverage it to create customer value
Provide input to the business and Labs leadership on long-term AI strategy
Mentor and coach scientists and engineers on best practices and foster innovation, collaboration, and continuous learning
Design and deliver AI solutions using NLP, information retrieval, machine learning, and generative AI
Use information retrieval techniques, prompting workflows, model training, and evaluation design to build and optimize solutions

Requirements

What you’ll need

PhD in a relevant discipline or master’s plus a comparable level of experience
7+ years of hands-on experience building NLP / IR systems for commercial applications
Experience writing production code and ensuring well-managed software delivery
Demonstrable experience translating complex problems into successful AI applications
Professional experience scaling yourself and leading through others in an applied research setting
Outstanding communication, problem-solving, and analysis skills
Staying up to date with the latest research and emerging technology for generative AI for NLP and IR
Experience collaborating with Product, Engineering and other business stakeholders in an agile manner
Solid understanding of classic ML techniques used for NLP problems
Solid understanding of DL approaches used for NLP tasks such as transformer-based models
Working understanding of inner workings of large language models
Experience working on text-heavy NLP projects
Practical experience curating and optimizing datasets for evaluation of ML and LLM-based solutions, including AutoEval methods
Practical experience using generative AI technologies, including prompt engineering, in-context learning, chain-of-thoughts, prompt optimization, auto-evaluation, function calling, and controlled generation
Practical experience using RAG frameworks, pre-training/fine-tuning language models, and data curation/generation for training/fine-tuning language models
Practical experience using agentic frameworks such as PydanticAI, LangGraph, AutoGen, and Semantic Kernel
Proficiency in Python, Git, AWS, and Azure for remote model development and deployment
Experience building lightweight UIs, iterating on greenfield concepts, applying agile development practices, and rapid prototyping
Preferred: prior experience working on legal AI systems or solutions interacting with long documents
Preferred: experience building applications for the legal domain
Preferred: knowledge in legal, compliance, or regulatory domains; law degree (J.D.); paralegal experience
Preferred: publications at relevant venues such as ACL, EMNLP, NAACL, NeurIPS, ICLR, SIGIR, ICML, KDD, or similar
Preferred: knowledge of MLOps and the end-to-end lifecycle of software applications involving AI models

Benefits

Comp & perks

Work from anywhere for up to 8 weeks per year
Flexible vacation
Two company-wide Mental Health Days off
Access to the Headspace app
Retirement savings
Tuition reimbursement
Employee incentive programs
Resources for mental, physical, and financial wellbeing
Two paid volunteer days off annually
Opportunities to get involved with pro-bono consulting projects and ESG initiatives
Flexible work arrangements
Career development and continuous learning through Grow My Way programming
Supportive workplace policies through Flex My Way