Applied Scientist
Thomson Reuters is a leading information and technology company seeking an Applied Scientist to develop and implement machine learning and AI solutions for their legal, tax, and regulatory domains. The role involves collaborating with product and engineering teams to deliver impactful solutions while learning from domain experts.
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, and 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
- Flexibility & Work-Life Balance
- Career Development and Growth
- Industry Competitive Benefits
- Social Impact
Company Overview
Company H1B Sponsorship