Research Engineer - TR Labs

Do you love creating innovative solutions for customers? Then come and apply your skills and passion for technology at Thomson Reuters Labs. We are seeking a Research Engineer who will bring expertise in AI and ML and is interested in building data‑driven capabilities that transform the way legal, accounting, and government professionals work across the globe. As a member of Thomson Reuters Labs in London, you will have a direct impact on our company and develop products and features that will delight our customers.

We experiment, we build, we deliver. We obsess over our customers through applied research and development of new products and technologies. In TR Labs, we act fast and learn fast, innovating collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News.

As a Research Engineer at Thomson Reuters Labs, you will be part of a global interdisciplinary team of experts. We hire engineers and specialists across a variety of AI research areas to drive the company’s digital transformation. The science and engineering of AI are rapidly evolving. We are looking for an adaptable learner who can design with the customer in mind, think in code, and likes to learn and develop new skills as they are needed;

someone comfortable with jumping into new problem spaces.

Is this you? Come join us!

• Develop and Deliver:
  Applying modern software development practices, you will be involved in the entire software development lifecycle, designing, building, testing and delivering high‑quality solutions.
• Build Scalable ML Solutions:
  You will create large scale data processing pipelines to help researchers build and train novel machine learning algorithms. You will develop high performing scalable systems in the context of large online delivery environments.
• Be a Team Player:
  Working in a collaborative team‑oriented environment, you will share information, value diverse ideas, and partner with cross‑functional and remote teams.
• Be an Agile Person:
  With a strong sense of urgency and a desire to work in a fast‑paced, dynamic environment, you will deliver timely solutions.
• Be Innovative:
  You are empowered to try new approaches and learn new technologies. You will contribute innovative ideas, create solutions, and be accountable for end‑to‑end deliveries.
• Be an Effective Communicator:
  Through dynamic engagement and communication with cross‑functional partners and team members, you will effectively articulate ideas and collaborate on technical developments.

Essential skills & experience

• A Bachelor of Science degree, computer science or related field
• At least 2 years software engineering experience, ideally in the context of machine learning and natural language processing
• Experience and understanding of Python software development stacks and ecosystems, ideally also experience with other programming languages and ecosystems.
• Ability to understand, apply, integrate and deploy Machine Learning capabilities and techniques into other systems.
• Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit‑learn
• Take pride in writing clean, reusable, maintainable and well‑tested code
• Ad here to learn and embrace new and emerging technology
• Familiarity with probabilistic models and understand the mathematical concepts underlying machine learning methods

Preferred skills & experience

• Proficiency in automation, system monitoring, and cloud‑native applications, with familiarity in AWS or Azure (or a related cloud platform)
• Previous exposure to Natural Language Processing (NLP) problems and have familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, etc.
• Ability to understand and translate between language and methodologies used both in research and engineering fields
• Ability to take and integrate Machine Learning solutions to production‑grade software

• 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…