We are seeking an experienced and dynamic MLOps Engineer to join our Analytics team. As a highly motivated MLOps Engineer with strong organizational and technical skills, you will leverage predictive models, machine learning, and generative AI to drive business insights and facilitate informed decision-making. Your contributions will help Thomson Reuters rapidly scale data-driven initiatives and create revenue opportunities for our stakeholders.
About the Role:
In this opportunity as MLOps Engineer:
Define, manipulate, aggregate and use both structured and unstructured big data in order to support descriptive and predictive analytics across the businesses.
Collaborate with scientists, product groups and content groups to perform big data aggregations, symbology mapping, and manipulations of important data-sets.
Perform statistical (and machine learned) analyses on data to serve business purposes.
Narrate stories (sometimes to a non-technical audience) about our content and processes by data analysis and visualization.
Define and develop software for the analysis and manipulation of large and very large data-sets.
Guide the architecture of big-data business processes with an eye towards robustness, parsimony and reproducibility (at senior levels).
About You:
You re a fit for the role of MLOps Engineer if your background includes:
2+ years of proven experience as a MLOps Engineer or in a similar role.
The role requires the candidate to work from 12 pm - 9 pm IST.
Bachelor s / Master s degree in computer science, Data Science, Machine Learning, or a related quantitative field.
Proven hands-on experience in generative AI in areas such as prompt engineering, experience in designing, building and maintaining a MLOps environment.
Develop and communicate the overall application architecture in a distributed cloud environment, including patterns, best practices, and guidelines.
Experience in data modeling for applications leveraging advanced analytic query generation typically found in descriptive queries.
Competently performs well-defined analytical tasks without extensive intervention.
Develops hypotheses and investigates them independently.
Developing judgment as to how best to maximize return on research investment for a given project.
Excellent communication skills.
Strong analytical capabilities.
Successful record of leading and inspiring cross-functional teams
Excellent time management, communications, decision-making, presentation, and organization skills.