Senior Product Manager, Autodesk

• Bachelor’s degree in Computer Science, Engineering, Data Science, or a related field
• 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
• Data and analytics ecosystems
• 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
• Demonstrated ability to improve technical-user workflows and drive execution in ambiguous environments
• Strong product judgment, communication, and cross-functional collaboration skills

Desirable

• As an ML Platform Product Manager, you will help define and execute the roadmap for the Autodesk Machine Learning Platform (AMP), focused on accelerating how ML engineers and data scientists build, operationalize, and scale AI systems across Autodesk
• You will partner closely with platform engineers, ML engineers, and data scientists to improve end-to-end workflows spanning data exploration, experimentation, model deployment, inference, and downstream AI integration. This role is centered on reducing operational friction, improving experimentation velocity, and building cohesive platform experiences for technical practitioners
• We are looking for a technically fluent, execution-oriented product manager who is passionate about improving complex AI/ML workflows and productizing scalable platform capabilities
• Define and execute roadmap priorities for the Autodesk ML Platform with a focus on workflow acceleration, interoperability, and practitioner productivity
• Improve end-to-end operational workflows across:
• Data discovery and exploration
• Experimentation and model iteration
• Model deployment and inference
• Downstream AI integration
• Partner closely with ML engineers, data scientists, and platform engineers to identify workflow bottlenecks and simplify complex operational systems
• Help shape scalable platform capabilities related to:
• Model deployment
• Inference services
• AI/ML observability
• Foundation model and generative AI support
• Drive platform interoperability across data platforms, ML tooling, deployment systems, and analytics ecosystems
• Establish intuitive “golden path” workflows that improve usability while maintaining flexibility for advanced use cases
• Analyze platform usage, workflow friction, and practitioner feedback to drive continuous product improvement
• Collaborate with cross-functional teams to drive platform adoption through strong product experiences and measurable workflow improvements
• Stay current on evolving AI platform, LLMOps, inference, and developer tooling trends