FactSet
Machine Learning Engineer – Hybrid (Neo4j, NLP, Chatbot, Cloud)
Job Description
Join FactSet’s Data Solutions AI team as an Machine Learning 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:
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Architect and design groundbreaking machine learning techniques tailored to financial tasks within Knowledge Graphs, creating innovative solutions that extend beyond traditional applications.
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Enhance and scale our AWS-based infrastructure to ensure the efficient, reliable delivery of ML and AI solutions, including the integration of LLM.
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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.
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Manage the entire software development lifecycle, from the initial design and coding through to testing and the deployment of financial AI applications.
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Construct and maintain robust data pipelines capable of processing complex structured and unstructured financial data, guaranteeing the highest quality inputs for our models.
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Act as a mentor to team members, promoting a culture of innovation and continuous learning within the team.
Minimum Requirements:
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2+ years of profound software engineering experience, significantly focused on AI/ML solutions in production environments.
Skills:
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Demonstrated expertise in cloud architecture (primarily AWS) and familiarity with a broad range of services.
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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.
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Proficient in Python, with strong skills in Docker and API development.
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Excellent communication abilities, capable of engaging both technical and business audiences alike, and leading cross-functional projects.
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Knowledge of major database architectures including MongoDB, SQL, NoSQL, and Vector databases.
Additional/Desired Skills:
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Experience with Knowledge Graphs and architecting LLM-powered solutions.
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Deep familiarity with the financial data, its applications, and specific industry challenges.
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Expertise in NLP libraries such as nltk and SpaCy and proficiency in unstructured text analysis.
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Demonstrable leadership capabilities and experience in mentoring or leading a team.
Education:
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An MS degree in Machine Learning, Computer Science, or a related field is preferred.
Key Technologies:
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Python
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Deep Learning Frameworks: Tensorflow, Keras, PyTorch
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NLP/Chatbot Technologies
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Cloud Platforms: AWS, Azure
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Graph Technology: Neo4j
Why Join Us?
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High-Impact Work: Your work will directly impact how financial professionals globally make pivotal decisions.
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Collaborative, Innovative Team: Collaborate with top-tier engineers and scientists to advance the frontier of financial AI.
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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.