Director, Artificial Intelligence & Machine Learning

Director of Artificial Intelligence & Machine Learning

• 'Midwest based' Client is a global ecommerce retailer ( household brand ) with 000s of stores and majority sales via digital channels
• ONSITE preferred
• Base 20% Bonus 30% annual stock grants
• Role Reports to VP – Data & AI and it oversees 20 reports ( 3 direct ) in ML and AI
• Looking for someone that started in more technical roles, moved their way up and then ultimately into more ‘strategy’ type role but with that technical foundational knowledge - large cloud platforms (e.g., AWS, Azure, GCP); Python-based data and ML ecosystems, containerization, and ideally Databricks like platforms
• Ability to lead teams leveraging large-scale cloud-native solutions

We are entering a pivotal phase in our data transformation and AI/ML journey. We're seeking a leader who can drive strategy and lead change and not just execute pre-existing plans. This role is about bridging legacy systems with future-state AI/ML capabilities and driving adoption. We are seeking a transformative leader to define and execute our enterprise AI/ML strategy and establish a world-class Center of Excellence (COE).

The Director of AI & ML leads the enterprise’s ML & AI Development and Engineering Center of Excellence (COE), as its senior most member, serving as the central force behind our AI strategy, engineering, execution, and innovation. You will set the vision, architect scalable platforms, and lead a high-performing team to deliver production-grade solutions. From traditional machine learning models to generative AI and agentic systems, you’ll ensure solutions are secure, sustainable, and aligned with business priorities. This position calls for a blend of strategic leadership and hands-on technical depth—someone who can inspire, influence, and execute at scale.

What You’ll Do

Lead Enterprise AI Strategy

• Lead the AI /ML COE, define and evolve the AI/ML roadmap, aligning with business objectives and emerging technologies.
• Act as a champion for responsible AI and enterprise-wide enablement.

Drive Transformation

• Bridge traditional systems with modern AI capabilities.
• Embed AI/ML into core business processes—not just pilots—while managing budget priorities and stakeholder expectations.

Build & Scale the COE

• Recruit, mentor, and grow a top-tier engineering organization.
• Establish best practices for ML Ops, model lifecycle governance, and platform scalability.

Innovate with Generative AI

• Lead development of advanced GenAI and agentic systems working alongside the ‘GenAI product owner’ and ‘Data engineering’ team. Stay at the forefront of the GenAI ecosystem—evaluating open-source and proprietary models (e.g., LLaMA, Phi)

Deliver Production-Grade Models

• Empower Data Scientists to transform models into reliable, governed, and scalable AI systems; allowing them to focus on experimentation while ML engineers ensure delivery
• Implement automation and reusable infrastructure to accelerate deployment and reduce time-to-value.

Engineering Execution

• Oversee design and deployment of AI pipelines, custom agents, and ML platforms. Ensure seamless productionization of models that are accomplished in python and deployed as containers or onto Databricks.
• Ensure seamless productionization of models that is primarily accomplished in python and deployed as containers or onto Databricks using modern engineering practices including Ci/CD and cloud-native architecture.

Influence at leadership level Partner with data engineering, data science, and architecture teams to deliver integrated solutions.

• Partner with senior leadership and major business units (Supply Chain, Finance, HR, Tech) to drive adoption and investment.
• Navigate concerns around automation and job displacement with a compelling vision for value creation

What We’re Looking For

Required

• Bachelor’s or Master’s in Computer Science, Engineering, or related field.
• 10 years in AI/ML, including 5 years in senior leadership roles.
• Proven experience delivering enterprise-scale ML systems in production.
• Expertise in ML Ops, model deployment, AI platform architecture, and cloud-native engineering.
• Hands-on experience with Generative AI, LLMs, and multi-agent systems (e.g., MCP, A2A).
• Strong foundation in Python, containerization, ideally Databricks and large cloud platforms (AWS, Azure, GCP).
• Ability to lead teams leveraging large-scale cloud-native solutions
• Exceptional communication and stakeholder management skills.

Preferred

• Experience as a strategic change agent scaling AI capabilities in large, matrixed organizations.
• Background in embedding AI/ML into business processes and driving adoption and resolve tensions.
• Experience with both open-source and proprietary AI models.
• Familiarity with responsible AI practices and governance.
• Recognized contributions to the AI/ML community (e.g., publications, open-source projects, speaking engagements).
• PhD in a relevant technical field.