Nathan Frank

Speaking & Media

I regularly speak about ML platform engineering, enterprise AI adoption, and technology leadership at conferences, podcasts, and industry events.

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

Featured Appearances

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 Search AI Assistants RAG Knowledge Management Onyx Open 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.
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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.
MLOps SRE/DevOps Production ML ML Engineering Team Dynamics DevX
Audience: Engineering leaders, ML platform teams, and DS/MLEs shipping models at scale.
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All Media

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 Strategies TDD Python Pandas/NumPy PySpark pytest Data Validation CI/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.
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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.
MLOps Production ML SRE/DevOps Team Collaboration
Audience: Leaders and practitioners building and operating ML systems in production, including data scientists, ML engineers, product managers, SRE and DevOps teams.
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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.