Python Lead Research Engineer

Lead Research Engineer

Do you love creating innovative solutions for customers?

We are seeking a passionate Lead Research Engineer who will bring expertise in AI and ML and is interested in building data‑driven capabilities that drive transformation. As a member of Thomson Reuters Labs you will have a direct impact on our company by helping to create new and innovative capabilities that will delight our customers.

What does Thomson Reuters Labs do?

• We experiment, we build, we deliver.
• We support the organization and our customers through applied research and the development of new products and technologies.
• TR Labs innovates collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News.

As a Lead 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 think in code and likes to learn and develop new skills as they are needed;

someone comfortable with jumping into new problem spaces; who enjoys directing and supporting the efforts of others.

• Be a Leader
  :
  Provide technical leadership partnering with other engineers to develop and improve methodology and evolve the technology stack.
• Develop and Deliver
  :
  Apply modern software development practices, you will be involved in the entire software development lifecycle, building, testing and delivering high‑quality solutions.
• Build Scalable ML Solutions
  :
  Create large‑scale data processing pipelines to help researchers build and train novel machine‑learning algorithms; develop high‑performing scalable systems in the context of large online delivery environments.
• Be a Team Player
  :
  Work in a collaborative, team‑oriented environment, share information, value diverse ideas, 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, deliver timely solutions.
• Be Innovative
  :
  Empowered to try new approaches and learn new technologies, 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, effectively articulate ideas and collaborate on technical developments.

Essential skills & experience

• A Bachelor's Degree in Computer Science or Related Field.
• At least 8 years of software engineering experience, including at least 2 years working on a machine‑learning related product or solution.
• Experience leading technical work streams within a software engineering organization.
• Skilled with Python software development stacks; experience with other programming languages and ecosystems is ideal.
• Ability to integrate and deploy machine‑learning capabilities and techniques into other systems.
• Familiar with the Python data science stack (Num Py, Sci Py, Pandas, Dask, spaCy, NLTK, scikit‑learn).
• Take pride in writing clean, reusable, maintainable and well‑tested code.
• Proficient in automation, system monitoring, and cloud‑native applications; familiarity with AWS or Azure is preferred.
• Proficient in system analysis and design; consider Dev Ops and automation as fundamental pillars.
• Desire to learn and embrace new and emerging technology.
• Demonstrate adaptability and thrive in a dynamic environment, successfully managing and delivering high‑quality results when faced with fluid requirements.
• Familiar with probabilistic models and understand the mathematical concepts underlying machine‑learning methods.
• Experience leading and/or mentoring teams.
• Experience providing guidance around roadblocks for the team.
• Experience providing updates to internal stakeholders.

Preferred skills & experience

• Experience integrating machine‑learning solutions into production‑grade software with a sound understanding of Model Ops and MLOps principles.
• Previous exposure to natural language processing (NLP) problems and familiarity with key tasks such…