Thomson Reuters
Thomson Reuters empowers professionals with cutting-edge technology solutions informed by industry-leading content and expertise.
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.
Is this you? Come join us!
About the Role
In this opportunity as a Lead Research Engineer, you will:
1. Be a Leader: Provide technical leadership partnering with other engineers to develop and improve methodology and evolve the technology stack.
2. Develop and Deliver: Applying modern software development practices, you will be involved in the entire software development lifecycle, building, testing and delivering high-quality solutions.
3. 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.
4. Be a Team Player: Working in a collaborative team-oriented environment, you will share information, value diverse ideas, partner with cross-functional and remote teams.
5. 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.
6. 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.
7. 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.
About You
You are a fit for the Lead Research Engineer role if your background includes:
Essential skills & experience:
1. A Bachelor's Degree in Computer Science or Related Field.
2. Significant software engineering experience.
3. Demonstrable experience working on a Machine Learning related product or solution.
4. Experience leading technical workstreams within a software engineering organization.
5. Deep understanding of Python software development stacks and ecosystems; experience with other programming languages and ecosystems is ideal.
6. Ability to understand, apply, integrate and deploy Machine Learning capabilities and techniques into other systems.
7. Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn.
8. Take pride in writing clean, reusable, maintainable and well-tested code.
9. Proficiency in automation, system monitoring, and cloud-native applications, with familiarity in AWS or Azure (or a related cloud platform).
10. Proficient in system analysis and design; consider DevOps and automation as fundamental pillars of your work.
11. A desire to learn and embrace new and emerging technology.
12. Familiarity with probabilistic models and understanding of the mathematical concepts underlying machine learning methods.
13. Experience leading and/or mentoring teams.
14. Experience providing guidance around roadblocks for the team.
15. Experience providing updates to internal stakeholders.
Preferred skills & experience:
1. Experience integrating Machine Learning solutions into production-grade software with a sound understanding of ModelOps and MLOps principles.
2. Previous exposure to Natural Language Processing (NLP) problems and familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, etc.
3. Experience successfully taking and integrating Machine Learning solutions to production-grade software.
What's in it For You?
You will join our inclusive culture of world-class talent, where we are committed to your personal and professional growth through:
* Hybrid Work Model: We’ve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role).
* Wellbeing: Comprehensive benefit plans; flexible and supportive benefits for work-life balance; flexible vacation; two company-wide Mental Health Days Off; work from another location for up to a total of 8 weeks in a year; Headspace app subscription; retirement, savings, tuition reimbursement, and employee incentive programs.
* Culture: Globally recognized and award-winning reputation for equality, diversity and inclusion, flexibility, work-life balance, and more.
* Learning & Development: LinkedIn Learning access; internal Talent Marketplace with opportunities to work on projects cross-company.
* Social Impact: Employee-driven Business Resource Groups; two paid volunteer days annually; Environmental, Social and Governance (ESG) initiatives.
* Purpose Driven Work: We help our customers pursue justice, truth and transparency.
Do you want to be part of a team helping re-invent the way knowledge professionals work? How about a team that works every day to create a more transparent, just and inclusive future? At Thomson Reuters, we’ve been doing just that for almost 160 years...
Accessibility: As a global business, we rely on diversity of culture and thought to deliver on our goals.
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