Lead Engineer, AI Solutions

Are you excited about working at the forefront of applied research in an industry setting? Thomson Reuters Labs  is seeking a Lead Engineer to help maximize the impact of R&D investment and guide the delivery of cutting-edge AI solutions from concept to production.

 
What does Thomson Reuters Labs do? We experiment, we build, we deliver. We support the organization and our customers through applied research in informational retrieval, natural language processing and generative AI. We work closely with product and domain experts to identify compelling solutions at the intersection of user need and technical feasibility. Our team is designing the next generation of research technology for Legal and Tax Professionals globally. We drive AI innovation for Thomson Reuters’ Core Research Products, including Westlaw, Practical Law, and Checkpoint. 

 
About the Role 
 
Our Lead Engineers are responsible for the design and delivery of AI solutions that enhance Thomson Reuters' products. This role has particular focus on system design and data architecture for customer facing applications of large language models and modern information retrieval. In this role, you will: 
 

• Lead the design and architecture of scalable AI solutions, including human-in-the-loop data generation, model training and evaluation workflows 

• Develop and implement strategies to integrate AI technologies across production platforms, applying best practices in cloud native development 

• Evaluate and recommend tools, frameworks, and technologies for AI projects 

• Promote efficient collaboration between scientists and engineers 

• Ensure that AI solutions comply with industry standards and regulations  

• Foster a culture of innovation, growth, and continuous improvement 

 
 
About You 
 
You’re a fit for the role of Lead Engineer if your background includes: 
 

• A bachelor's degree in computer science or related field.  

• Experience leading technical workstreams within a software engineering organization.  

• Deep understanding of Python software development stacks and ecosystems; experience with other programming languages and ecosystems is ideal.  

• Experience in the development, testing, and deployment of ML solutions 

• Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn.  

• Writing clean, reusable, maintainable and well-tested code.  

• Proficiency in automation, system monitoring, and cloud-native applications, with familiarity in AWS or Azure (or a related cloud platform).  

• A desire to learn and embrace new and emerging technology.  

• Experience leading and/or mentoring teams, providing technical guidance and communicating results to internal stakeholders.  

  
Preferred Skills & Experience:  
 

• Experience integrating Machine Learning solutions into production-grade software with a sound understanding of ModelOps and MLOps principles and the ability to translate between language and methodologies used both in research and engineering fields   

• Prior exposure to Natural Language Processing (NLP) concepts and applications 

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