Lead Machine Learning Engineer
at FactSet
Posted 6 days ago
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Lead AI/ML Engineer on FactSet's Data Solutions AI team to drive the evolution of financial AI applications. Design and implement ML/NLP solutions across knowledge graphs, NLP, predictive analytics, and large language models, deploying them in production on AWS. Own end-to-end software delivery from design to testing and deployment, build robust data pipelines for complex financial data, and mentor team members. Collaborate with data scientists and ML engineers to select models and deployment strategies, and scale infrastructure for high performance.
FactSet creates flexible, open data and software solutions for over 200,000 investment professionals worldwide, providing instant access to financial data and analytics that investors use to make crucial decisions.
At FactSet, our values are the foundation of everything we do. They express how we act and operate, serve as a compass in our decision-making, and play a big role in how we treat each other, our clients, and our communities. We believe that the best ideas can come from anyone, anywhere, at any time, and that curiosity is the key to anticipating our clients’ needs and exceeding their expectations.
Team Impact
FactSet's Data Solutions AI team seeks a seasoned Lead AI/ML Engineer to drive the evolution of our financial AI applications. You'll bring your substantial expertise to bear in developing and deploying cutting-edge solutions that leverage Graph Technologies, NLP, predictive analytics, Large Language Models, and cloud-native technologies. If you have a passion for solving complex financial domain problems and a track record of delivering high-performance AI systems, this is an exceptional opportunity to make a significant impact.
What You’II Do
Lead Innovation: Design and architect new machine learning approaches specifically tailored to financial tasks across Knowledge Graphs, going beyond adaptation to invent novel solutions.
Cloud & Infrastructure Mastery: Optimize and scale our AWS-based infrastructure for high-performance, reliable delivery of ML and AI solutions, including LLM integration.
Strategic ML/NLP Deployment: Collaborate with data scientists and ML engineers to seamlessly integrate and manage a range of ML and NLP models in production environments. Provide guidance on model selection and deployment strategies.
End-to-End Ownership: Take responsibility for the full software development lifecycle, from design and coding to testing and deployment of financial AI applications.
Data Expertise: Develop and maintain robust data pipelines for complex structured and unstructured financial data, ensuring the highest quality inputs for our models.
Mentorship & Collaboration: Share your knowledge and mentor team members, fostering a culture of innovation and continuous learning.
What We’re Looking For
7+ years of in-depth software engineering experience, with a significant portion focused on AI/ML solutions in production environments.
Demonstrated expertise in cloud architecture (AWS) and a range of associated services.
Strong command of Natural Language Processing/Machine Learning/Deep Learning concepts and their applications, with a proven track record of successful model development and deployment.
Advanced proficiency in Python, Docker, and API development.
Excellent communication skills, able to bridge technical and business audiences and lead cross-functional initiatives.
Familiarity with major database architectures (MongoDB, SQL, NoSQL, Vector)
Desired Skills
MS degree preferred in Machine Learning, Computer Science, or a related discipline.
Experience with Knowledge Graphs.
Experience architecting and scaling LLM-powered solutions.
Deep understanding of financial data, applications, and domain-specific challenges.
Expertise in NLP libraries (nltk, SpaCy) and unstructured text analysis.
Proven leadership skills and experience mentoring or managing a team.
What's In It For You
At FactSet, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a FactSetter means:
The opportunity to join an S&P 500 company with over 45 years of sustainable growth powered by the entrepreneurial spirit of a start-up.
Support for your total well-being. This includes health, life, and disability insurance, as well as retirement savings plans and a discounted employee stock purchase program, plus paid time off for holidays, family leave, and company-wide wellness days.
Flexible work accommodations. We value work/life harmony and offer our employees a range of accommodations to help them achieve success both at work and in their personal lives.
A global community dedicated to volunteerism and sustainability, where collaboration is always encouraged, and individuality drives solutions.
Career progression planning with dedicated time each month for learning and development.
Business Resource Groups open to all employees that serve as a catalyst for connection, growth, and belonging.
Learn more about our benefits here.
Salary is just one component of our compensation package and is based on several factors including but not limited to education, work experience, and certifications.
Company Overview:
FactSet (NYSE:FDS | NASDAQ:FDS) helps the financial community to see more, think bigger, and work better. Our digital platform and enterprise solutions deliver financial data, analytics, and open technology to more than 8,200 global clients, including over 200,000 individual users. Clients across the buy-side and sell-side, as well as wealth managers, private equity firms, and corporations, achieve more every day with our comprehensive and connected content, flexible next-generation workflow solutions, and client-centric specialized support. As a member of the S&P 500, we are committed to sustainable growth and have been recognized among the Best Places to Work in 2023 by Glassdoor as a Glassdoor Employees’ Choice Award winner. Learn more at www.factset.com and follow us on X and LinkedIn.
At FactSet, we celebrate difference of thought, experience, and perspective. Qualified applicants will be considered for employment without regard to characteristics protected by law.
