Director, Machine Learning & Artificial Intelligence
Director, Machine Learning & Artificial Intelligence
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1 Vacancy
Job Description
The Director of Machine Learning & Artificial Intelligence (ML & AI) leads the enterprises 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 systemsfrom traditional ML models to cutting-edge generative AI agentsensuring 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 Responsibilities
COE Leadership & Strategy
- Lead the ML & AI Center of Excellence as the enterprises 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 organizations 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 levelsfrom exploratory notebooks to advanced prototypesinto 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 acceleratorremoving 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 ecosystemevaluating 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.
Qualifications :
Required
- Bachelors or Masters 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 Information :
Location: Role will sit at our HQ in Ann Arbor MI and relocation package will be provided for qualified candidate. Must be willing to relocate if not in the Ann Arbor area
Hybrid Schedule- Onsite Monday-Thursday and work from anywhere on Fridays
Benefits:
- 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
All your information will be kept confidential according to EEO guidelines.
Remote Work :
No
Employment Type :
Full-time
Employment Type
Full-time
