Senior AI/ML Scientist

About this role

Responsibilities:  

Solve Business Problems with AI  

• 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.  

Design & Build Agentic AI Solutions  

• 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.  

Scalable & Responsible AI  

• 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.  

Thought Leadership & Collaboration  

• 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.  

Qualifications:  

• 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.  

• 0 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.  

Special Factors Sponsorship Vanguard is not offering visa sponsorship for this position. About Vanguard At Vanguard, we don't just have a mission—we're on a mission.

To work for the long-term financial wellbeing of our clients. To lead through product and services that transform our clients' lives. To learn and develop our skills as individuals and as a team. From Malvern to Melbourne, our mission drives us forward and inspires us to be our best.

How We Work Vanguard has implemented a hybrid working model for the majority of our crew members, designed to capture the benefits of enhanced flexibility while enabling in-person learning, collaboration, and connection. We believe our mission-driven and highly collaborative culture is a critical enabler to support long-term client outcomes and enrich the employee experience.

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