Director, Machine Learning & Artificial Intelligence

Domino's Pizza-posted 3 months ago
Full-time • Senior
Hybrid • Ann Arbor, MI
5,001-10,000 employees
Food Services and Drinking Places
Resume
Match Score
Upload and Match ResumeTrack Jobs with Teal

The 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.

  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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.
  • 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).
  • 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
Track Jobs with Teal

Job Search Resources

•
AI Resume Builder
•
Director of Machine Learning Resume Examples
•
Cover Letter Examples

Tools

Career Hubs

Guides

Company

© 2024 Teal Labs, Inc
Privacy PolicyTerms of Service