Machine Learning Engineer - Hybrid (Neo4j, NLP, Chatbot, Cloud)
London, GBR
FactSet
FactSet provides business data to power your workflow, valuable market analytics to help you outperform, and global market insights to give you perspective.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:
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:
2+ 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.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: API Development APIs Architecture AWS Azure Chatbots Computer Science Data pipelines Deep Learning Docker Engineering Keras LLMs Machine Learning ML models MongoDB Neo4j NLP NLTK NoSQL Pipelines Python PyTorch spaCy SQL TensorFlow Testing
Perks/benefits: Career development
More jobs like this
Explore more career opportunities
Find even more open roles below ordered by popularity of job title or skills/products/technologies used.