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Factset

Software Engineer: Intelligent Platform (Conversational AI)

Job Posted 17 Days Ago Posted 17 Days Ago
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London, Greater London, England
Mid level
London, Greater London, England
Mid level
Develop and maintain AWS-based infrastructure for ML and NLP applications, integrate LLMs for conversational AI, and collaborate with cross-functional teams.
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FactSet, a leading provider of financial information and analytics, helps the world’s best investment professionals outperform. We've been recognized as one of FORTUNE's 100 Best Companies to Work for and a Best Workplace in the United Kingdom and France. Headquartered in Norwalk, CT, with over 9,600 employees worldwide and offices across North America, Europe, and Asia Pacific, FactSet has achieved $1.4 billion in annual revenues.

The Opportunity:

FactSet's Machine Learning team seeks team seeks a skilled Software Engineer to help us build and optimize the infrastructure powering our cutting-edge AI-driven financial applications. You'll have the opportunity to work with Natural Language Processing (NLP), Large Language Models (LLMs), and cloud technologies to create transformative solutions.

What will you be doing?

Cloud & Infrastructure Development Design, deploy, and maintain a robust AWS-based infrastructure tailored for serving ML, NLP, and LLM-powered applications.

LLM Integration & Federation: Play a key role in integrating LLMs and developing conversational AI systems that seamlessly interact with our existing ML workflows.

Model & Application Deployment Collaborate with data scientists and ML engineers to deploy and maintain machine learning models and applications in production environments.

Software Engineering Excellence: Produce clean, well-tested, and scalable code. Develop dashboards and visualizations that make complex financial data accessible to our clients.

Data Management: Engineer efficient pipelines to ingest, analyze, and process both structured and unstructured financial data.

Cross-Team Collaboration: Partner effectively with other Engineering teams to ensure the success of shared projects.

Minimum Requirements:

  • 3+ years of hands-on software engineering experience in production environments.

Critical Skills:

  • Expertise in AWS cloud architecture and services (ECS, EC2, S3, Athena, Glue, etc.)
  • Strong foundation in C#, Python, Docker, and API development.
  • Familiarity with Search, ML/NLP concepts and experience working with ML teams.
  • Excellent problem-solving skills and collaborative mindset.

Highly Desirable/Additional Skills:

  • Experience integrating Large Language Models and developing conversational AI solutions.
  • Familiarity with deep learning libraries (Keras, PyTorch, TensorFlow)
  • Experience with data processing tools (Pyspark, Hive) and databases (MongoDB, SQL, NoSQL)
  • NLP expertise (nltk, SpaCy), especially with unstructured financial data.
  • Understanding of financial applications and terminology.

Education:

  • BS or MS in Computer Science, Mathematics, or a related field.

Why Join Us?

Impactful Work: Shape the future of financial AI by contributing to high-visibility, client-facing applications.

Innovative Environment: Be at the forefront of AI development, pushing the boundaries of LLMs and conversational AI.

Supportive Team: Collaborate with world-class engineers and data scientists passionate about solving complex problems.

At FactSet, we celebrate diversity of thought, experience, and perspective. We are committed to disrupting bias and a transparent hiring process.  All qualified applicants will be considered for employment regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. FactSet participates in E-Verify. 

FactSet is an Equal Opportunity Employer – M/F/Veteran/Disability/Sexual Orientation/Gender Identity 

Top Skills

AWS
C#
Docker
Hive
Keras
Ml/Nlp
MongoDB
NoSQL
Pyspark
Python
PyTorch
Spacy
SQL
Tensorflow,Nltk

Factset London, England Office

One Snowden Street, , London, United Kingdom, EC2A 2DQ,

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