Research Engineer

Thomson Reuters Schaffhausen, Schaffhouse – Suisse Publié le 24/09/2026
Description du poste
Overview

As a Research Engineer at Thomson Reuters Labs, you apply AI/ML expertise to build data-driven capabilities for legal, tax, accounting, and government professionals. You will work in a global, interdisciplinary team to design, build, and deliver scalable ML solutions that impact customers worldwide. You’ll experiment with new ideas, ship end-to-end features, and collaborate across functions in a fast-paced environment. This role offers hands-on work with cutting-edge research used to transform how professionals work.

Leistungen / Benefits
  • Hybrid work model
  • Flexible vacation and work-life balance
  • Mental health days and wellbeing resources
  • Tuition reimbursement
  • 401k with company match
  • Employee stock purchase plan
Verantwortungsbereiche
  • Design, build, test, and deliver high-quality software solutions across the full lifecycle
  • Create large-scale data processing pipelines and train novel ML algorithms
  • Collaborate with cross-functional and remote teams in a team-oriented environment
  • Work in a fast-paced, agile setting with a sense of urgency
  • Contribute innovative ideas and take end-to-end ownership of deliveries
  • Communicate effectively with technical and non-technical stakeholders
Zentrale Anforderungen
  • BS in Computer Science or related field
  • ≥2 years software engineering experience with ML and NLP
  • Proficiency in Python software development; exposure to other languages
  • Ability to deploy ML capabilities into production systems
  • Familiarity with Python scientific libraries: NumPy, SciPy, Pandas, Dask, spaCy, NLTK, scikit-learn
  • Clean, maintainable, well-tested code
  • Willingness to learn and adapt to new tech
  • Familiarity with probabilistic models and ML theory
  • Experience with cloud platforms (AWS or Azure)
  • Exposure to NLP tasks such as NER, Information Extraction, Information Retrieval
  • Ability to translate research ideas to engineering implementations
  • Production-oriented mindset for integrating ML into software
  • Collaborative mindset
  • Strong communication
  • Curiosity and willingness to learn
  • Python
  • NLP
  • Machine Learning
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