Director of Artificial Intelligence

Hirewell • Full-time • Greater Chicago Area, US • 5d ago

Our partner is seeking an experienced, visionary, and hands-on Director of AI to lead their Artificial Intelligence strategy and execution. This leader will oversee the development and deployment of AI and machine learning models across our client's platform, working closely with product, engineering, and data teams to drive innovation, customer value, and business outcomes. This high-impact leadership role requires a blend of strategic thinking, deep technical expertise, and operational excellence.

Key Responsibilities

Define and drive our client’s AI strategy, aligned with business objectives and product roadmap.
Evangelize the use of AI/ML across the organization and with our clients.
Build, lead, and mentor a high-performing team of AI scientists, machine learning engineers, and data experts.
Foster a culture of innovation, collaboration, and continuous learning.
Partner with Product and Engineering teams to integrate AI into core and new product offerings, including predictive ETAs, risk alerts, exception management, and automation.
Ensure scalable, production-grade ML models that are explainable, reliable, and efficient.
Lead research efforts on cutting-edge AI technologies such as generative AI, LLMs, graph learning, and causal inference.
Stay abreast of academic and industry trends to maintain a competitive edge.
Oversee MLOps, data pipelines, and model lifecycle management.
Define KPIs for AI performance and impact; ensure governance, fairness, and compliance.
Engage with key clients, partners, and internal stakeholders to identify opportunities, gather feedback, and demonstrate value.
Represent our client in industry forums, conferences, and research partnerships.

Qualifications (Must-Have)

Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
10+ years of experience in AI/ML, with at least 3-5 years in a leadership role.
Proven experience building and deploying large-scale AI systems in production.
Deep expertise in supervised and unsupervised learning, time series forecasting, NLP, generative AI, or reinforcement learning.
Strong programming and data engineering skills (Python, TensorFlow/PyTorch, Spark, etc.).
Experience with MLOps, data governance, and scalable infrastructure.
Ability to translate business problems into AI solutions with measurable outcomes.

Preferred

Experience in logistics, supply chain, or transportation tech domains.
Familiarity with LLM fine-tuning, Retrieval-Augmented Generation (RAG), and vector search.
Contributions to open source, patents, or research publications in top AI venues.