Senior AI/ML Scientist

The Vanguard Group•Charlotte, PA

1d•Hybrid

About The Position

Vanguard is seeking a Senior AI/ML Scientist to solve business problems using AI. This role involves designing and building advanced ML models, enterprise knowledge systems, and agentic AI solutions. The scientist will partner with business stakeholders to identify and prioritize high-value problems addressable by Agentic AI, LLMs, and ML. A key focus will be on defining and implementing business-centric evaluation frameworks that measure coverage, relevance, trustworthiness, explainability, and user adoption, in addition to technical model performance. The role also includes collaborating with engineering teams for scalable and responsible AI deployment, implementing evaluation and monitoring for LLM and agentic systems, and acting as a thought leader and trusted AI advisor. Vanguard operates on a hybrid working model, emphasizing a mission-driven and collaborative culture.

Requirements

Agentic AI: Experience designing AI agents that reason, plan, and act across systems.
Large Language Models (LLMs): Hands-on experience building enterprise LLM applications (e.g., RAG, tool use, orchestration, evaluation).
Natural Language Processing (NLP): Strong experience working with unstructured text and language-driven workflows.
ML: Hands on experience with Gradient Boosting methods, familiar with preeminent hyper-parameter tuning and interpretability options.
MS or PhD in Computer Science, Machine Learning, Data Science, or a related quantitative field.
3+ years delivering AI/ML solutions in production environments.
5+ years of hands-on Python experience; experience with distributed data processing is a plus.
Strong ability to solve business problems using AI, not just build models.
Excellent communication skills, with the ability to explain complex concepts to both technical and non-technical audiences.
Experience working in cross-functional, enterprise environments.

Responsibilities

Design and build advanced ML models that integrate multi-dimensional data into insights and signals that drive critical business decisions.
Design and build enterprise knowledge systems that integrate structured and unstructured data across multiple business platforms, enabling AI agents to retrieve, reason over, and operationalize trusted organizational knowledge.
Partner with business stakeholders to identify, frame, and prioritize high-value problems that can be addressed using Agentic AI, LLMs, and ML.
Define and implement business-centric evaluation frameworks that measure coverage, relevance, trustworthiness, explainability, and user adoption in addition to technical model performance.
Focus on business outcomes, not just model performance.
Architect and develop agentic AI systems that can reason, plan, and take actions across tools, workflows, and data sources.
Design multi-agent and tool-augmented LLM solutions to automate complex, multi-step processes.
Ensure solutions are reliable, explainable, and governed for enterprise use.
Collaborate with engineering teams to deploy AI solutions with scalability, security, and performance in mind.
Implement evaluation, monitoring, and guardrails for LLM and agentic systems, including bias, drift, and failure modes.
Align solutions with enterprise risk management, compliance, and responsible AI standards.
Act as a trusted AI advisor, helping teams understand where Agentic AI and LLMs add value—and where they do not.
Contribute to AI best practices, reusable patterns, and strategic direction.
Mentor peers and teammates on applied AI and business-driven problem solving.