Machine Learning Engineer building AI/ML systems and enhancing data connections at FactSet. Collaborating in a hybrid team to drive innovations in financial data processing.
Responsibilities
Build new systems to ingest and enrich data into an ontology.
Monitor and enhance the accuracy, performance, and observability of our GenAI RAG stack.
Evaluate new large language models, tools, and AI engineering techniques.
Improve query planning, optimization, and evaluation infrastructure.
Partner and collaborate with product development leads to identify technical requirements for future product enhancements.
Collaborate with teams across the organization to understand their data.
Requirements
3+ years 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.
Working knowledge of Natural Language Processing/Machine Learning/Deep Learning concepts and their applications, with a proven track record of successful model development and deployment.
Proficiency in Python, Docker, and API development.
Strong technical writing and presentation skills
Familiarity with relational databases and data modeling techniques.
Bachelor’s degree in computer science, computer engineering, or similar technical field or equivalent practical experience
Benefits
Competitive salary
Flexible working hours
Professional development opportunities
Health insurance
Paid time off
Retirement plans
Job title
Machine Learning Engineer – Python, Docker, API Development, AI/ML Solutions
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