Research Engineer
United States of America, Eagan, MinnesotaAll locationsUnited States of America, Eagan, MinnesotaCanada, Toronto, OntarioUnited States of America, New York, New YorkUnited States of America, Ann Arbor, MichiganUnited Kingdom, LondonSwitzerland, Zug, ZugUnited States of America, Frisco, Texas Hybrid
$101,600 a yearJobFig found this opening at its original source and checks that it remains available.
About the role
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, you will have a direct impact on our company and develop products and features that will delight our customers. As a Research Engineer at Thomson Reuters Labs, you will be part of a global interdisciplinary team of experts. In this opportunity as a Research Engineer , you will: Applying modern software development practices, you will be involved in the entire software development lifecycle, designing, building, testing and delivering high-quality 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.
What you'll bring
- 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.
- A Bachelor of Science degree, computer science or related field
- At least 2 years software engineering experience
- Experience and understanding of Python software development stacks 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
- A desire to learn and embrace new and emerging technology