Speaking & Media

I'm Nathan Frank — Director of ML Platform & Operations at Grainger, where I lead the platform and teams helping data science, ML engineering, and analytics teams ship faster. My background spans astrophysics, sports technology, and enterprise ML platforms, which means I translate comfortably between researchers, engineers, and business stakeholders. I speak about production ML systems, enterprise AI adoption, and the organizational realities of scaling AI in large companies.

Nathan Frank speaking at GTG Tech Conference

Topics I Cover

  • ML Platform Strategy: Building platforms that data science and engineering teams actually want to use
  • Enterprise AI Adoption: Practical approaches to scaling AI initiatives across large organizations
  • Technology Leadership: Leading technical teams through complex platform transformations
  • MLOps & Platform Engineering: Production-grade ML infrastructure and operations

Talks & Appearances

Modernizing Legacy Systems with Applied AI

Panel at Tech in Motion Chicago •
A panel discussion with Chicago tech leaders on driving AI innovation in legacy industries—scaling solutions, reshaping enterprise roles, and operating AI systems responsibly.
Applied AILegacy ModernizationEnterprise AIAI at ScaleResponsible AI
Audience: Engineering leaders, architects, and technologists working in established enterprises looking to adopt and scale AI.
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Ctrl+F for the Enterprise: Because "Where Was That Again?" Shouldn't Be a Daily Question

Talk at GTG Tech Conference •
Why centralized enterprise search matters and how to do it right. Introduces Onyx, an open-source, AI-powered search and assistant piloted at Grainger, with real-world deployment insights.
Enterprise SearchAI AssistantsRAGKnowledge ManagementOnyxOpen Source
Audience: Team leads, product managers, and technical stakeholders (platform/IT, data/ML, security/architecture) who want faster, trusted answers across internal tools, docs, and conversations.

Testing Patterns for Data and Machine Learning

Workshop at GTG Tech Conference •
A hands-on workshop for Python data and ML practitioners on bringing software testing discipline to the PyData/PySpark stack. Covers sensible defaults, project setup, and real-world patterns.
Testing StrategiesTDDPythonPandas/NumPyPySparkpytestData ValidationCI/CD
Audience: Data scientists, ML engineers, and data engineers working in Python/PySpark who want practical, copy-pasteable testing patterns to improve quality and speed.

Challenges Operationalizing ML (And Some Solutions)

Podcast at MLOps Community •
A concise guide to taking ML from experiment to production with an SRE/DevOps mindset. It clarifies what is unique to MLOps and how to start with paved road patterns that scale.
MLOpsSRE/DevOpsProduction MLML EngineeringTeam DynamicsDevX
Audience: Engineering leaders, ML platform teams, and DS/MLEs shipping models at scale.
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Challenges Operationalizing Machine Learning (And Some Solutions)

Talk at GTG Tech Conference •
Demystifies MLOps by mapping it to proven DevOps and SRE practices while highlighting what is unique to machine learning. Covers workflow pitfalls, team communication, and simple starting points.
MLOpsProduction MLSRE/DevOpsTeam Collaboration
Audience: Leaders and practitioners building and operating ML systems in production, including data scientists, ML engineers, product managers, SRE and DevOps teams.

Speaking Availability

I'm available for:

  • Conference presentations and keynotes
  • Panel discussions and fireside chats
  • Podcast interviews
  • Workshop facilitation
  • Corporate speaking engagements

Get in Touch

Interested in having me speak at your event or on your podcast? I'd love to hear from you! Reach out through LinkedIn or email with details about your event, audience, and preferred topics.