Senior Product Manager, Ai/ml Platform

Autodesk Autodesk · Enterprise · Toronto, ON +1

Product Manager for an ML Platform (AMP) at Autodesk, focused on accelerating ML engineer and data scientist workflows for building, operationalizing, and scaling AI systems. The role involves improving end-to-end processes from data discovery to model deployment and inference, and supporting foundation models and generative AI.

What you'd actually do

  1. Define and execute roadmap priorities for the Autodesk ML Platform with a focus on workflow acceleration, interoperability, and practitioner productivity
  2. Improve end-to-end operational workflows across: - data discovery and exploration - experimentation and model iteration - model deployment and inference - downstream AI integration
  3. Partner closely with ML engineers, data scientists, and platform engineers to identify workflow bottlenecks and simplify complex operational systems
  4. Help shape scalable platform capabilities related to: - model deployment - inference services - AI/ML observability - foundation model and generative AI support
  5. Drive platform interoperability across data platforms, ML tooling, deployment systems, and analytics ecosystems

Skills

Required

  • Product management experience focused on ML platforms, AI infrastructure, developer platforms, or technical workflow products
  • Understanding of machine learning systems and lifecycle workflows
  • Understanding of data and analytics ecosystems
  • Understanding of model deployment and operational AI systems
  • Familiarity with modern AI approaches including foundation models and generative AI
  • Experience working closely with ML engineers, data scientists, or platform engineering teams
  • Ability to improve technical-user workflows
  • Ability to drive execution in ambiguous environments
  • Product judgment
  • Communication skills
  • Cross-functional collaboration skills

Nice to have

  • Experience with AI/ML platforms supporting experimentation, deployment, or inference workflows
  • Familiarity with modern data platforms and query ecosystems (e.g., Snowflake, Trino)
  • Experience improving developer or practitioner productivity through platform design
  • Exposure to AI observability, evaluation, or workflow automation systems

What the JD emphasized

  • 3+ years of product management experience focused on ML platforms, AI infrastructure, developer platforms, or technical workflow products
  • Strong understanding of: machine learning systems and lifecycle workflows
  • Experience working closely with ML engineers, data scientists, or platform engineering teams
  • Demonstrated ability to improve technical-user workflows and drive execution in ambiguous environments

Other signals

  • ML Platform
  • operationalize AI systems
  • end-to-end workflows
  • model deployment
  • inference