At a Glance
- Tasks: Join us as a Research Engineer to innovate and develop cutting-edge machine learning solutions.
- Company: Thomson Reuters Labs is a leader in AI research, transforming industries with data-driven solutions.
- Benefits: Enjoy flexible work arrangements, comprehensive benefits, and a culture of continuous learning.
- Why this job: Be part of a diverse team tackling real-world challenges in legal, tax, and news sectors.
- Qualifications: A relevant technical degree and experience in applied machine learning are essential.
- Other info: Contribute to impactful projects while enjoying a hybrid work model and social impact initiatives.
The predicted salary is between 36000 - 60000 £ per year.
Are you a curious and open-minded individual with an interest in state-of-the-art machine learning engineering and research? Thomson Reuters Labs is seeking a Data Engineer with a passion for solving challenging machine learning problems in a data-rich, complex and innovative environment.
What does Thomson Reuters Labs do? We experiment, we build, we deliver. We support the organization and our product teams through foundational research and development of new products and technologies. The Labs innovate collaboratively across our core segments in Legal, Tax & Accounting, Government, and Reuters News. We undertake a diverse portfolio of projects while investing in long-term research for the future.
As a Research Engineer, you will be part of a diverse global team of experts. We hire world-leading specialists in SWE /Applied ML, as well as Research, to drive the company’s leading internal AI model development, fueled by an unprecedented wealth of data and powered by cutting-edge technical infrastructure. You will have the opportunity to contribute to a data curation & filtering system combining the best of real-world scalable data processing systems combined with the latest insights into what training data leads to the best LLMs.
Thomson Reuters Labs is known for consistently delivering successful data-driven Artificial Intelligence solutions in support of high-growth products that serve Thomson Reuters customers in new and exciting ways.
About the Role: In this opportunity as a Research Engineer - Data, you will:
- Innovate: You will work at the very cutting edge of AI Research at an institution with some of the richest data sources in the world. Through your work, you will help us make the best use of this resource, in a dynamic flywheel that connects data collection & annotation with model training and expert evaluation, helping us continuously improve our training data. You will also develop novel performance-driven data sub-selection methods together with the latest training insights from our researchers.
- Engineer and Develop: Design, develop, and optimize scalable data pipelines to support LLM training and evaluation. You will also help us develop this in a robust and testable way, through careful source control and a solid back-up system for various data versioning methods.
- Collaborate: Working on a collaborative global team of engineers and scientists both within Thomson Reuters and our academic partners at world-leading universities. In addition, you will work closely with world experts in the legal domain, which can provide feedback to your work and/or evaluate your outputs or annotate training data.
About You: You're a fit for the role of Research Engineer - Data, if your background includes:
- Required qualifications: Relevant degree in a technical discipline. Interest in & experience working with (applied) machine learning, e.g. few-shot learning with out-of-the-box language models, training of smaller NLP classifiers, etc. Excellent programming, debugging and system design skills. Excellent communication skills to report and present software designs and findings clearly, both orally and in writing. Curious and innovative disposition capable of devising novel, well-founded algorithmic solutions to relevant problems. Self-driven attitude and ability to work with limited supervision. Experience with relational and NoSQL databases (e.g., PostgreSQL, MySQL, MongoDB, Cassandra). Experience with data pipeline orchestration tools. Experience with cloud-based data platforms such as AWS, GCP, or Azure (e.g., S3, BigQuery, Azure Data Lake Storage). Comfortable working in fast-paced, agile environments, managing uncertainty and ambiguity.
- Preferred qualifications: Additional legal knowledge as evidenced by a degree or interest in the legal domain. Ability to communicate with multiple stakeholders, including non-technical legal subject matter experts. Experience with big data technologies such as Spark, Hadoop, or similar. Experience conducting world-leading research, e.g. by contributions to publications at leading ML venues. Previous experience working on large-scale data processing systems. Strong software and/or infrastructure engineering skills, as evidenced by code contributions to popular open-source libraries.
What’s in it For You? Join us to inform the way forward with the latest AI solutions and address real-world challenges in legal, tax, compliance, and news. Backed by our commitment to continuous learning and market-leading benefits, you’ll be prepared to grow, lead, and thrive in an AI-enabled future.
- Industry-Leading Benefits: We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing.
- Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, and hybrid model, empowering employees to achieve a better work-life balance.
- Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrow’s challenges and deliver real-world solutions. Our skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future.
- Culture: Globally recognized and award-winning reputation for inclusion, innovation, and customer-focus. Our eleven business resource groups nurture our culture of belonging across the diverse backgrounds and experiences represented across our global footprint.
- 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 delivering a seamless experience that is digitally and physically connected.
- Social Impact: Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives.
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. Our industry-leading products and services include highly specialized information-enabled software and tools for legal, tax, accounting and compliance professionals combined with the world’s most global news services – Reuters. We help these professionals do their jobs better, creating more time for them to focus on the things that matter most: advising, advocating, negotiating, governing and informing. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments that celebrate diversity and inclusion. At a time when objectivity, accuracy, fairness and transparency are under attack, we consider it our duty to pursue them.
Accessibility: As a global business, we rely on diversity of culture and thought to deliver on our goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity/Affirmative Action Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law.
Research Engineer, Data (Foundational Research, Machine Learning) employer: Thomson Reuters
Contact Detail:
Thomson Reuters Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer, Data (Foundational Research, Machine Learning)
✨Tip Number 1
Familiarise yourself with the latest advancements in machine learning, particularly in areas like few-shot learning and NLP classifiers. This will not only enhance your understanding but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of AI and data engineering. Attend relevant conferences or webinars where you can meet experts from Thomson Reuters Labs or similar organisations, as personal connections can often lead to job opportunities.
✨Tip Number 3
Showcase your experience with cloud-based platforms like AWS, GCP, or Azure by working on personal projects or contributing to open-source initiatives. This practical experience can set you apart from other candidates.
✨Tip Number 4
Prepare to discuss your problem-solving approach and any innovative solutions you've developed in past projects. Being able to articulate your thought process clearly will demonstrate your fit for the collaborative environment at Thomson Reuters Labs.
We think you need these skills to ace Research Engineer, Data (Foundational Research, Machine Learning)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning and data engineering. Emphasise your programming skills, experience with databases, and any projects that showcase your ability to solve complex problems.
Craft a Compelling Cover Letter: In your cover letter, express your passion for machine learning and how it aligns with Thomson Reuters Labs' mission. Mention specific projects or technologies you’ve worked on that relate to the role, and demonstrate your curiosity and innovative mindset.
Showcase Communication Skills: Since excellent communication is key for this role, include examples of how you've effectively communicated technical concepts to non-technical stakeholders. This could be through presentations, reports, or collaborative projects.
Highlight Collaborative Experience: Thomson Reuters values collaboration, so mention any experience working in diverse teams or partnerships with academic institutions. Discuss how you contributed to team success and what you learned from those experiences.
How to prepare for a job interview at Thomson Reuters
✨Show Your Curiosity
As a Research Engineer, curiosity is key. Be prepared to discuss your interest in machine learning and how you've approached complex problems in the past. Share examples of projects where you explored innovative solutions.
✨Demonstrate Technical Skills
Make sure to highlight your programming and system design skills during the interview. Be ready to discuss specific technologies you've worked with, such as cloud platforms or data pipeline orchestration tools, and how they relate to the role.
✨Communicate Clearly
Excellent communication is crucial, especially when collaborating with diverse teams. Practice explaining your technical work in simple terms, so non-technical stakeholders can understand your contributions and findings.
✨Prepare for Collaboration Questions
Since this role involves working closely with both engineers and legal experts, think about your past experiences in collaborative environments. Be ready to share how you’ve successfully worked with others to achieve common goals.