Software Engineer (Python, TypeScript, API) at FactSet creating generative AI applications. Collaborating on data enrichment and enhancing the infrastructure for financial analytics.
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Hybrid Machine Learning Engineer – Python, Docker, API Development, AI/ML Solutions
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About the role
- 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
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