Machine Learning Engineer - (Python, NLP, AWS, API, Docker) - Hybrid

FactSet, a leader in financial information and analytics, is renowned for empowering investment professionals to excel. Celebrated as one of FORTUNE's 100 Best Companies to Work For and recognized as a Best Workplace in both the United Kingdom and France, FactSet stands out for its global presence and performance. Our headquarters is in Norwalk, CT, with a dedicated workforce of over 9,600 employees across North America, Europe, and Asia Pacific. FactSet consistently demonstrates financial robustness with an impressive $1.4 billion in annual revenues.

Job Description:

Join FactSet's Data Solutions AI team as an AI/ML Engineer to drive forward-thinking innovations in our financial AI applications. Your extensive expertise in deploying state-of-the-art solutions including Graph Technologies, NLP, predictive analytics, Large Language Models (LLM), and cloud-native technologies will be crucial. This role is perfect for someone with a passion for tackling complex problems within the financial domain and has a proven ability to deliver robust, high-performance AI systems.

Key Responsibilities:

• Architect and design groundbreaking machine learning techniques tailored to financial tasks within Knowledge Graphs, creating innovative solutions that extend beyond traditional applications.

• Enhance and scale our AWS-based infrastructure to ensure the efficient, reliable delivery of ML and AI solutions, including the integration of LLM.

• Work closely with data scientists and ML engineers to integrate and manage diverse ML and NLP models within production environments effectively. Offer expert advice on model selection and deployment strategies.

• Manage the entire software development lifecycle, from the initial design and coding through to testing and the deployment of financial AI applications.

• Construct and maintain robust data pipelines capable of processing complex structured and unstructured financial data, guaranteeing the highest quality inputs for our models.

• Act as a mentor to team members, promoting a culture of innovation and continuous learning within the team.

Minimum Requirements:

• 3-5 years of profound software engineering experience, significantly focused on AI/ML solutions in production environments.

Skills:

• Demonstrated expertise in cloud architecture (primarily AWS) and familiarity with a broad range of services.

• Solid understanding of Natural Language Processing/Machine Learning/Deep Learning fundamentals and their real-world applications, evidenced by a successful history of model development and deployment.

• Proficient in Python, with strong skills in Docker and API development.

• Excellent communication abilities, capable of engaging both technical and business audiences alike, and leading cross-functional projects.

• Knowledge of major database architectures including MongoDB, SQL, NoSQL, and Vector databases.

Additional/Desired Skills:

• Experience with Knowledge Graphs and architecting LLM-powered solutions.

• Deep familiarity with the 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

Why Join Us?

• High-Impact Work: Your work will directly impact how financial professionals globally make pivotal decisions.

• Collaborative, Innovative Team: Collaborate with top-tier engineers and scientists to advance the frontier of financial AI.

• Focus on Growth: FactSet is dedicated to continuous learning and offers ample opportunities for professional development.

Join us to push the boundaries of financial analytics and technology, harnessing your skills to make a significant impact in the industry.