Lead Applied Scientist, Search & Information Retrieval

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🕒 Outubro 14

🌐 Estados Unidos, Canadá – Remoto

🇺🇸 Estados Unidos – Remoto (EUA) 🇨🇦 Canadá – Remoto

🗽 New York – Remoto

🗽 New York – Remote

💵 $147.600 - $274.200 / ano

⏰ Tempo Integral

🟠 Sênior

🧬 Cientista Pesquisador(a)

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Thomson Reuters

SiteLinkedInTodas as Vagas

10.000+ funcionários

Fundada em 2008

💼 Consultoria

⚖️ Jurídico

🛡️ Seguros

Consulting • Legal • Insurance

A Thomson Reuters é uma empresa global de conteúdo e tecnologia que oferece a profissionais soluções confiáveis e precisas nos setores jurídico, fiscal e de contabilidade, comércio internacional e gestão de riscos. A companhia disponibiliza um portfólio que inclui ferramentas de pesquisa jurídica, software de preparação fiscal, soluções de compliance e regulatórias, além de serviços de mídia, como a Reuters, para notícias globais. Com investimentos significativos em IA generativa, a Thomson Reuters segue inovando para ajudar profissionais a otimizar seus fluxos de trabalho e aprimorar a tomada de decisão. Suas plataformas atendem a diversos segmentos — como escritórios de advocacia, corporações, profissionais da área tributária e organizações de mídia —, fornecendo ferramentas essenciais que combinam tecnologia poderosa com conteúdo especializado aprofundado.

Descrição

• Own the design, development, and production deployment of large-scale search and information retrieval systems powering Westlaw, Practical Law, CoCounsel, and next-generation Thomson Reuters search experiences • Design and deploy search architectures for 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 traditional information retrieval 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 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 • Publish research and measure success through shipped, production-performing systems

🎯 Requisitos

• 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 • Experience with PyTorch, Hugging Face Transformers, and distributed model development • Knowledge of search engine architecture, indexing systems, and ingestion pipelines • Experience building ranking and re-ranking systems • Knowledge of information retrieval, semantic retrieval, hybrid retrieval, and vector search architectures • Knowledge of query understanding, relevance optimization, and search evaluation methodologies • Experience with retrieval systems supporting large collections of text-rich content • Experience with LLM-enhanced retrieval, RAG architectures, and retrieval optimization • Experience with end-to-end measurement and evaluation of search quality and user outcomes • Experience with legal, regulatory, tax, scientific, or other text-heavy domains preferred • Experience building retrieval systems over large enterprise knowledge repositories preferred • Experience with Elasticsearch, OpenSearch, Solr, Vespa, or similar search technologies preferred • API platform development and self-service search platforms experience preferred • Experience with agentic AI systems incorporating retrieval capabilities preferred • Experience with AzureML or AWS SageMaker preferred • Experience building systems combining search, retrieval, and document understanding capabilities preferred

🏖️ Benefícios

• Flexible work arrangements, including work from anywhere for up to 8 weeks per year • Flexible vacation • Two company-wide Mental Health Days off • Headspace app access • Retirement savings • Tuition reimbursement • Employee incentive programs • Resources for mental, physical, and financial wellbeing • Two paid volunteer days off annually • Comprehensive health, dental, vision, disability, and life insurance programs (United States) • 401k plan with company match (United States) • Sick and safe paid time off • Paid holidays • Parental leave • Sabbatical leave • Flexible Spending and Health Savings Accounts • Fitness reimbursement • Employee Assistance Program • Group Legal Identity Theft Protection benefit • 529 Plan access • Commuter benefits • Adoption & Surrogacy Assistance • Employee Stock Purchase Plan • Potential eligibility for an Annual Bonus based on enterprise and individual performance