MassMutual's Data Science team is seeking an impact-driven Lead AI Engineer to join our high-performing, cross-functional team. In this role, you will lead the design and deployment of advanced AI solutions that drive strategic decision-making and business transformation. You'll apply cutting-edge techniques in machine learning, generative AI, and large language models (LLMs) to solve complex, high-value problems across the enterprise.
This is a unique opportunity to work alongside experts in applied mathematics, statistics, computer science, and physics-collaborating on initiatives that shape the future of MassMutual and the life insurance industry at large.
Overall Responsibilities:
Architect and lead end-to-end ML/AI solutions s upporting various use cases for a large enterprise using LLMs, deep learning, and probabilistic modeling-from ideation to production .
Deploy scalable GenAI and Agentic AI systems that directly support business goals.
Establish and promote best practices in AI development and responsible AI deployment .
Drive innovation by identifying emerging technologies and translating research into practical applications.
Collaborate with engineering teams to build robust, production-grade AI pipelines and APIs.
Prototype and deliver AI-powered applications (e.g., web apps, dashboards, visualizations) that enable data-driven decisions.
Influence senior leadership by aligning AI initiatives with enterprise strategy and communicating insights effectively.
Mentor and develop junior talent , fostering a culture of technical excellence and continuous learning.
Candidate Requirements:
Recognized industry expertise in AI/ML, with a track record of delivering impactful solutions.
7+ years of experience in data science, machine learning, or AI engineering roles.
Deep understanding of machine learning, statistics, NLP, optimization, and LLMs.
Hands-on experience with AI deployment and orchestration frameworks and protocols (e.g., MLflow , llama-index, MCP ).
Extensive experience testing LLM behavior across a variety of foundation models and benchmarks.
Experience building AI-powered applications and collaborating with software engineers and product managers.
Strong programming skills in Python. Proficiency in R is a plus.
Proficiency in SQL and database design ; familiarity with cloud-native data platforms , vector databases, and semantic search is a plus.
Exceptional communication skills , with the ability to explain complex concepts to non-technical stakeholders.
Education:
M.S. or Ph.D. in Computer Science, Statistics, Applied Mathematics, Electrical Engineering, Physics, or a related quantitative field.
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