Software Engineer

FactSet is seeking a Software Engineer with experience in AWS cloud architecture, infrastructure deployment and maintenance. The SSE 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.
What will you be doing?
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
Who you are?
You have BS or MS in Computer Science or Mathematics related field.
You have 5+ years of working experience as a software engineer
You have experience with AWS and cloud-based infrastructure
You have familiarity with ML and NLP
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
Prior experience with Docker and API development
Experience with AWS environment [SageMaker, S3, Athena, Glue, ECS, EC2]
It is great if you have:
Prior experience with RDFs, triple stores, and relation extraction
Experience working with large volumes of data in a stream or batch processing environment.
Usage of MongoDB
Familiarity with deep learning libraries (Keras, PyTorch, Tensorflow)
Familiarity with big data tool chain (e.g. Pyspark, Hive)
Experience with information extraction, parsing and segmentation,
Knowledge of ontologies, taxonomy resolution and
disambiguation.
Experience in Unsupervised Learning techniques Density Estimation, Clustering and Topic Modelling.
Graph database experience (AWS Neptune, Neo4j)
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 practicesin a production environment
FactSet creates flexible, open data and software solutions for tens of thousands of investment professionals around the world, providing instant access to financial data and analytics that investors use to make crucial decisions. Join a team of highly motivated, talented individuals who are empowered to find answers through creative technology. Spread the news! We understand the importance of connections, which is why we have launched an external referral pilot program in the United States. If you are a partner, customer, or vendor; you are now able to refer top talent for a monetary reward. Please note some exclusions may apply*
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