Engineering Manager, Data Science and Machine Learning

This job is with Morningstar, an inclusive employer and a member of my Gwork – the largest global platform for the LGBTQ+ business community. Please do not contact the recruiter directly.

As an Engineering Manager, AI & ML (Data Collection), you will play a vital role in   executing   the company's AI and machine learning initiatives with a strong focus on data collection technologies. This position will require deep technical   expertise   in unstructured data processing, data collection pipeline engineering, and a hands-on approach to managing and mentoring engineers. Your leadership will ensure that AI & ML data collection systems are developed and operationalized at the highest standards of performance, reliability, and security.

You will be working closely with individual contributors, ensuring that projects align with broader business goals and AI/ML strategies.

This role requires deep   engagement   in the design, development, and maintenance   of AI & ML models, solutions, architecture, and services  . You will need to provide strong technical direction, problem-solve complex technical challenges, and ensure that the team consistently delivers high-quality, scalable solutions  .
You will   leverage   your deep knowledge in areas such as advanced natural language processing (NLP)  , generative AI (GenAI)   and   large language models (LLMs),   ML Operations (  MLOps  ), data architecture,   data pipelines, and cloud-managed services  .

Your leadership will ensure that our AI/ML systems align with     global business strategies,   maintaining   seamless integration and high-performance standard  s  .
You will oversee the end-to-end lifecycle of AI/ML data systems-from research and development to deployment and operationalization  .

You will   be responsible for   mentoring team members, resolving technical challenges, and fostering a culture of innovation and collaboration   while   ensuring they have the right tools, frameworks, and guidance to succeed  .

This role offers a unique opportunity to drive impactful change in a fast-paced, dynamic environment, where your efforts will directly contribute to the success of our AI/ML initiatives globally  .
Your ability to collaborate with   cross-departmental stakeholders  , provide leadership across locations, set   high standards   for the team, and hire, train, and   retain   exceptional talent is foundational to your success. You will   solicit   feedback, engage others with empathy, inspire creative thinking, and help foster a culture of belonging, teamwork, and purpose  .

Team   Overview
You will lead a multidisciplinary team of engineers and data scientists responsible   for building AI & ML   solutions and   services   as part of robust   data collection pipelines   handling   large volumes of unstructured data. Your team will focus on building scalable and reliable systems to process and categorize data that is essential for downstream   data collection processing.

Outline of Duties and Responsibilities
AI & ML Data Collection Leadership    :
Drive the execution of AI & ML initiatives related to data collection, ensuring that the team's efforts are aligned with overall business goals and strategies.

Technical Oversight    :
Provide hands-on technical leadership in the engineering of ML models and services, focusing on unstructured data, NLP, and classifiers. Oversee and contribute to the implementation of scalable solutions that meet   high standards   of reliability and efficiency.

Team Leadership & Development    :
Lead, mentor, and develop a high-performing team of engineers and data scientists, fostering a culture of innovation and continuous improvement. Ensure effective communication and coordination within your team and across geographically dispersed teams.

NLP Technologies    :
Contribute to the development and application of NLP techniques, including classifiers, transformers, LLMs, and other methodologies, to efficiently process and categorize unstructured data. Ensure these models are integrated seamlessly into the broader AI/ML infrastructure.

Data Pipeline Engineering    :
Design, develop, and   maintain   advanced data collection…