Software Engineer, Factset

• You have BS or MS in Computer Science or Mathematics related field
• You have 3+ years of working experience as a software engineer
• You have experience with AWS and cloud-based infrastructure
• You have familiarity with ML, NLP and GenAI (including RAG, Prompt Engineering, Vector DBs)
• You have a successful history of writing production grade code and releasing in an enterprise environment
• You are a team player
• You have strong analytical skills
• You are fluent in English; you can communicate about complex subjects to non-technical stakeholders
• You are highly proficient in Python
• You are familiar with machine learning frameworks like sklearn and ML workflow
• You are 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

Desirable

• FactSet is seeking a Software Engineer with experience in AWS cloud architecture, infrastructure deployment and maintenance
• The Software Engineer will work with other engineers to serve applications with ML model implementations for NLP, classification and LLMs (Large Language Model)
• Necessary experience for this role would include knowledge of databases, APIs, Amazon Elastic Container Services (ECS) and other AWS services
• This role is in the Data Solutions AI team and reports to the VP, Director of Engineering
• The Software Engineer works with the team to develop a roadmap for management and growth of existing pipelines and infrastructure for serving ML and AI solutions
• Work may include deployment and maintenance of models, databases, and applications in addition to support work on various AI/ML projects that include entity and topic modeling, semantic tagging/enrichment, information extraction, transfer learning, graph neural networks, and integration of Large Language Models into existing ML frameworks
• Bring your experience within the team
• Manage and deploy various cloud-based infrastructure
• Participate to different projects as a software engineer
• Manage cloud infrastructure
• Make sure to align with business needs
• Deliver clean, well-tested code that is reliable, maintainable, and scalable
• Deploy working solutions
• Develop dashboards and other visualizations for financial experts
• Ingest and analyse structured and unstructured data
• Develop processes for data collection, quality assessment, and quality control
• Deploy and maintain ML and NLP models
• Keep up to date / share your passions
• Stay up to date with state-of-the-art approaches and technological advancement
• Share your passion for science, ML, technology, …
• Collaborate with other Engineering teams