Machine Learning Engineer - Python, SQL, NoSQL, and Vector databases

Location: Greater London

Fact Set 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.
** Your Team's Impact
** Join Fact Set's Data Solutions AI team where our mission is to transform how financial professionals discover and interact with data through cutting-edge AI and machine learning technologies. We're building intelligent systems that enable clients to ask natural language questions about financial data and receive actionable insights powered by our semantic enrichment platform. At the core of our infrastructure is a knowledge graph that connects financial concepts to Fact Set's comprehensive structured and unstructured data offerings, powering innovative solutions that push the boundaries of Fact Set’s products.
** What You'll Do
*** Scale our unstructured financial document enrichment pipeline that powers Fact Set’s knowledge graph to support the ingestion and enrichment of 500,000+ news, transcripts, and filings document chunks per day across dozens of financial domains.
* Enhance and scale our AWS-based infrastructure to ensure the efficient, reliable delivery of ML and AI projects, including the integration of agentic solutions.
* Work closely with other engineers and product developers to integrate and manage diverse domains of ML and NLP models. Offer expert advice on model selection and deployment strategies.
* In collaboration with agentic tooling (Claude Code, Cursor, CoPilot), manage the entire software development lifecycle, from the initial design and coding through to testing and the deployment of applications.
* Act as a mentor to team members, promoting a culture of innovation and continuous learning within the team.
** Note**:
Although we utilize agentic tools extensively at Fact Set (Claude Code, Cursor, Git Hub Copilot), we expect candidates for this role to demonstrate strong software engineering and machine learning fundamentals during the interview process.
** What We're Looking For
** You will be working on a team in a fast-paced environment where you will have the opportunity to influence the design and architecture of our products. An ideal candidate for the role would be an individual that has experience or a strong interest in working with data pipelines for unstructured data, a history of success deploying machine learning models to production, an interest in knowledge graph and semantic web technologies, and a passion for experimentation.
** Required Skills
*** 3-5 years of software engineering experience with significant focus on AI/ML solutions in production environments.
* Demonstrated expertise in cloud architecture, primarily AWS, with familiarity across a broad range of services.
* Strong understanding of Natural Language Processing, Machine Learning, and Deep Learning fundamentals with proven history of successful model development and deployment.
* Proficiency in Python, API development, and software engineering paradigms.
* Excellent communication abilities, capable of engaging both technical and business audiences and leading cross-functional projects.
* Knowledge of major database architectures including SQL, No

SQL, and Vector databases.
** Desired Skills
*** Experience with Knowledge Graphs and architecting LLM-powered solutions.
* Familiarity with financial data, applications, and specific industry challenges.
* Expertise in NLP libraries such as nltk and Spa Cy and proficiency in unstructured text analysis.
* Demonstrable leadership capabilities and experience in mentoring or leading a team.
** What's In It For You
** At Fact Set, our people are our greatest asset, and our culture is our biggest competitive advantage. Being a Fact Setter 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.
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