Job DescriptionThe Director of Machine Learning & Artificial Intelligence (ML & AI) leads the enterprise's ML & AI Development and Engineering Center of Excellence (COE), serving as the central force behind our AI strategy, execution, and innovation. This role is accountable for building and scaling the COE into a world-class capability hub that delivers production-grade AI/ML solutions across the business.
As the senior-most leader of the ML & AI COE, this individual will define the strategic roadmap, architect the technical foundation, and cultivate the talent and culture necessary to accelerate enterprise-wide AI adoption. They will oversee the development of intelligent systems-from traditional ML models to cutting-edge generative AI agents-ensuring solutions are scalable, sustainable, and aligned with business priorities.
This role requires a rare blend of visionary leadership and deep technical fluency. The ideal candidate is a builder and operator, equally comfortable setting bold direction and rolling up their sleeves to ensure delivery excellence.
Key ResponsibilitiesCOE Leadership & Strategy- Lead the ML & AI Center of Excellence as the enterprise's central engine for AI innovation, engineering, and enablement.
- Define and evolve the enterprise-wide ML & AI strategy in alignment with business goals and emerging technology trends.
- Serve as the organization's primary evangelist for responsible AI, driving awareness, education, and adoption across functions.
- Identify, prioritize, and champion high-impact AI opportunities that unlock business value and operational efficiency.
- Create resource plans, and track spend to budgets.
Team & Capability Building- Build and scale a high-performing ML & AI engineering organization, including hiring, mentoring, and org design.
- Foster a culture of innovation, experimentation, and continuous learning within the COE and beyond.
- Establish and enforce best practices for ML Ops, model lifecycle management, and platform scalability.
Model Enablement & Productionization- Empower data scientists by transforming models of all maturity levels-from exploratory notebooks to advanced prototypes-into robust, governed, and scalable production assets.
- Establish seamless handoff processes and shared tooling that allow data scientists to focus on experimentation and insight generation, while ML engineers ensure operational excellence, compliance, and long-term maintainability.
- Position the ML engineering function as a trusted partner and accelerator-removing friction, reducing time-to-value, and enabling faster iteration cycles through automation, observability, and reusable infrastructure.
GenAI & Agentic Systems Innovation- Collaborate closely with the enterprise GenAI enablement product owner to co-develop tailored agentic solutions that meet business needs and align with enterprise architecture and governance standards.
- Lead the development and integration of advanced generative AI capabilities, including tailored solutions. Working closely with consumers, and the Data engineering, quality and governance teams.
- Drive experimentation and rapid prototyping of intelligent agents that augment decision-making, automate workflows, and unlock new business capabilities. But prioritize and promote use cases that can drive real incremental value.
- Stay at the forefront of the GenAI ecosystem-evaluating open-source and proprietary models (e.g., LLaMA, Phi) and integrating them into scalable, secure, and responsible enterprise solutions.
Technical Execution & Engineering Excellence- Oversee the design, development, and deployment of custom AI agents, ML pipelines, and intelligent systems.
- Ensure seamless productionization of models with a focus on performance, reliability, and maintainability. This is primarily accomplished in python, and deployed as containers or onto databricks.
- Champion modern engineering practices such as containerization, CI/CD, and cloud-native infrastructure.
Cross-Functional Collaboration- Partner with Data Engineering, Data Science, and Solution Architecture COEs to ensure alignment and interoperability.
- Collaborate with business stakeholders to translate complex needs into scalable, value-driven AI solutions.
- Represent the ML & AI COE in enterprise governance, architecture, and innovation forums.
QualificationsRequired- Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field.
- 12+ years of experience in AI/ML, including 5+ years in a senior leadership role.
- Proven track record of delivering enterprise-scale ML systems in production environments.
- Deep expertise in ML Ops, model deployment, and AI platform architecture.
- Hands-on experience with GenAI technologies, LLMs, and multi-agent systems (e.g., MCP, A2A).
- Strong foundation in software engineering, cloud infrastructure, and containerization (e.g., Docker, Kubernetes).
- Exceptional communication, influence, and stakeholder management skills.
Preferred- PhD in a relevant technical field.
- Experience with both open-source and proprietary AI models.
- Familiarity with responsible AI practices, model governance, and ethical considerations.
- Experience scaling AI capabilities in large, matrixed organizations.
- Recognized contributions to the AI/ML community (e.g., publications, open-source projects, speaking engagements).
Additional InformationBenefits:
• Paid Holidays and Vacation
• Medical, Dental & Vision benefits that start on the first day of employment
• No-cost mental health support for employee and dependents
• Childcare tuition discounts
• No-cost fitness, nutrition, and wellness programs
• Fertility benefits
• Adoption assistance
• 401k matching contributions
• 15% off the purchase price of stock
• Company bonus
