Senior Manager Analytics - Artificial Intelligence R&d

Caterpillar Caterpillar · Industrial · Chicago, IL +2

Senior Manager to lead the Advanced Technology Pod within the AI R&D organization at Caterpillar. This role involves setting a technical vision for applied AI, defining and shaping AI initiatives, leading the design and delivery of production-intent prototypes and reference architectures, and managing a team of senior data scientists and AI engineers. The role also involves establishing R&D evaluation practices and partnering with various stakeholders.

What you'd actually do

  1. Set and evangelize a bold technical vision for applied AI at Caterpillar, anticipating where the technology is heading and where it can create the most value for our products, dealers, customers, and operators.
  2. Define and shape a portfolio of advanced AI initiatives that turn the vision into a focused set of high-impact opportunities for the pod.
  3. Lead the design and delivery of production-intent prototypes and reference architectures that are robust, well documented, and ready for handoff to engineering and platform teams responsible for productionization and MLOps.
  4. Define technical standards, patterns, and evaluation criteria that downstream teams can adopt to take AI R&D work to production with high fidelity.
  5. Partner with the Business POC Pod to advance promising use cases from rapid experimentation to production-intent prototypes, and with the Long-Term Research Pod to mature novel methods into applicable techniques.

Skills

Required

  • Effective communication skills, with the ability to simplify complex technical topics for executive audiences.
  • Solid statistical and experimental rigor for evaluating AI systems and guiding decision making
  • Ability to identify high-value AI opportunities and shape them into focused, actionable initiatives
  • Experience leading senior technical teams and setting a high technical bar through coaching, feedback, and standards.
  • Strong partnership skills to work across product, engineering, and external partners to influence direction and drive alignment.
  • Prior experience replacing or scaling a senior technical leader's scope, including stabilizing delivery while raising the technical bar.
  • Strong system-level thinking across data, models, and integration, with the ability to make sound architectural trade-offs
  • Deep understanding of how to translate research and experimentation into structured, production-intent prototypes and reference architectures
  • Strong expertise in modern AI methods, including large language models, generative systems, and advanced machine learning techniques
  • Master's degree in Computer Science, Engineering, Applied Mathematics, Statistics, or a related technical field; advanced degree preferred.
  • Significant experience leading applied AI or AI R&D teams that deliver production-intent prototypes and reference architectures for downstream engineering teams.
  • Strong command of Python-based ML stacks and modern AI frameworks, with a clear point of view on modeling standards, experimentation practices, and prototype quality.
  • Solid statistical foundation applied to AI experimentation, including A/B testing, significance, and rigorous measurement of accuracy, latency, cost, and safety in prototype settings.
  • Experience partnering with hyperscaler and hardware partners such as AWS, Microsoft and Azure, NVIDIA, or equivalent.
  • Familiarity with simulation and synthetic environments used to accelerate AI development for physical, real-world systems.
  • Track record of defining reference architectures, evaluation harnesses, and technical playbooks that downstream engineering and platform teams adopt to productionize AI.

Nice to have

  • Experience leading or contributing to de

What the JD emphasized

  • production-intent prototypes
  • reference architectures
  • productionization
  • MLOps
  • evaluation criteria
  • production-intent prototypes
  • Long-Term Research Pod
  • senior technical teams
  • production-intent prototypes
  • reference architectures
  • AI experimentation
  • prototype quality
  • AI experimentation
  • accuracy, latency, cost, and safety
  • reference architectures
  • evaluation harnesses
  • technical playbooks
  • productionize AI

Other signals

  • leading applied AI R&D teams
  • production-intent prototypes
  • reference architectures
  • advanced AI initiatives
  • leading a team of senior data scientists and AI engineers