Machine Learning Systems Research Intern at Red Hat working on AI inference and model optimization techniques. Collaborating with experts in the field while gaining hands - on experience in applied ML research.
About the role
- Software Engineer implementing machine learning models for various AI solutions at FactSet. Collaborating on cloud infrastructure management and serving ML applications for financial data.
Responsibilities
- Manage and deploy various cloud-based infrastructure
- Deliver clean, well-tested code that is reliable, maintainable, and scalable
- Develop dashboards and other visualizations for financial experts
- Ingest and analyze structured and unstructured data
- Develop processes for data collection, quality assessment, and quality control
- Deploy and maintain ML and NLP models
- Collaborate with other Engineering teams
Requirements
- BS or MS in Computer Science or Mathematics related field
- 3+ years of working experience as a software engineer
- Experience with AWS and cloud-based infrastructure
- Familiarity with ML, NLP and GenAI (including RAG, Prompt Engineering, Vector DBs)
- Successful history of writing production grade code and releasing in an enterprise environment
- Strong analytical skills
- Fluent in English; can communicate about complex subjects to non-technical stakeholders
- Highly proficient in Python
- Familiar with machine learning frameworks like sklearn and ML workflow
- Familiar with NLP libraries and text preprocessing (nltk, SpaCy, etc.)
- Experience with OpenAI, Llama, and other large language model frameworks.
- Prior experience working with unstructured data (text content, JSON records) including feature engineering experience from unstructured data.
- Working with Agile development practices in a production environment.
Benefits
- Health insurance
- 401(k) matching
- Flexible work hours
- Paid time off
- Professional development opportunities
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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