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Senior Financial AI Engineer

2 months ago

London, Greater London, United Kingdom FactSet Full time

About the Role

As a Senior Financial AI Engineer at FactSet, you will play a pivotal role in developing cutting-edge machine learning solutions that revolutionize financial decision-making. You'll be at the forefront of innovation, designing and implementing sophisticated algorithms to analyze complex financial data and deliver actionable insights.

Responsibilities

  • Architect and design groundbreaking machine learning techniques tailored for financial applications within Knowledge Graphs, pushing the boundaries of traditional AI solutions.
  • Enhance and scale our AWS-based infrastructure to ensure the efficient and reliable delivery of ML and AI solutions, including the integration of Large Language Models (LLMs).
  • Collaborate closely with data scientists and ML engineers to seamlessly integrate and manage diverse ML and NLP models within production environments. Provide expert guidance on model selection and deployment strategies.
  • Lead the entire software development lifecycle, from initial design and coding through rigorous testing and the deployment of innovative financial AI applications.
  • Construct and maintain robust data pipelines capable of processing vast amounts of structured and unstructured financial data, guaranteeing high-quality inputs for our models.
  • Mentor team members, fostering a culture of innovation and continuous learning within the engineering team.

Qualifications

  • 5-8 years of extensive software engineering experience, with a strong focus on AI/ML solutions deployed in production environments.

Critical Skills

  • Demonstrated expertise in cloud architecture (primarily AWS) and familiarity with a wide range of AWS services.
  • Experience with Knowledge Graphs and architecting LLM-powered solutions.
  • Solid understanding of Natural Language Processing/Machine Learning/Deep Learning fundamentals and their real-world applications, backed by a proven track record of model development and deployment.
  • Proficiency in Python, with strong skills in Docker and API development.
  • Excellent communication abilities, capable of effectively engaging both technical and business audiences, and leading cross-functional projects.
  • Knowledge of major database architectures including MongoDB, SQL, NoSQL, and Vector databases.

Additional/Desired Skills

  • Deep familiarity with financial data, its applications, and specific industry challenges.
  • Expertise in NLP libraries such as nltk and SpaCy, and proficiency in unstructured text analysis.
  • Demonstrable leadership capabilities and experience in mentoring or leading a team.

Education

  • An MS degree in Machine Learning, Computer Science, or a related field is preferred.

Key Technologies

  • Python
  • Deep Learning Frameworks: TensorFlow, Keras, PyTorch
  • NLP/Chatbot Technologies
  • Cloud Platforms: AWS, Azure
  • Graph Technology: Neo4j