Workflow Engineer

Job  
Location Burbank, California, United States Business The Walt Disney Studios Date posted Oct. 21, 2026

It’s the magic of immersing yourself in a motion picture masterpiece, or a new track from your favorite band, or the spectacle of a live Broadway show. It’s hard to define and even harder to create, but that’s what we do at The Walt Disney Studios. Ours is a culture of innovation, collaboration, and creativity. We raise the bar, then step over it, blazing trails through the production and distribution of world class entertainment around the globe.

If you want to help, tell compelling, enduring stories through movies, music, or stage plays, then we want to hear from you.

As part of the Studio Technology organization, you will join a group of seasoned technologists dedicated to solving a range of creative problems through innovation, strategy, and forward thinking. This role sits within the Motion Picture technologies at Walt Disney Studios, which is a group of specialty film making labs in Production Technology providing production services, research, development, innovation, and support required for civilized filmmaking.

Job Overview

As the Staff Workflow Engineer AIML, you have deep experience in production pipelines and hands-on AI/ML engineering expertise to design, prototype, and product ionize next-generation workflows for filmmaking.

This role bridges traditional pipeline engineering with emerging machine learning technologies. This role understands real-world production constraints and can translate cutting-edge AI capabilities into scalable, secure, production-ready solutions. You will report to the Director, Workflow Innovation within Motion Pictures Technologies in Burbank, CA.

Role & Responsibilities

• Design, prototype, and deploy end-to-end workflows supporting VFX, post-production, and emerging virtual production pipelines
• Integrate DCC applications (e.g., Nuke, Maya, Houdini) into automated and scalable systems
• Develop tools, APIs, and services that improve efficiency, quality, and cost
• Create proof-of-concept environments to simulate real production scenarios
• Document standards and best practices for operational adoption
• Evaluate, test, and integrate AI/ML models into production workflows
• Build and deploy ML pipelines (training, fine-tuning, inference, optimization)
• Work with foundation models (vision, audio, multimodal) and adapt them for production use.
• Optimize model performance for GPU environments and render farm deployment
• Collaborate with data scientists and ML engineers to transition research models into usable production tools
• Develop scalable backend services in Python and related frameworks
• Work with containerized environments (Docker, Kubernetes).
• Integrate GPU compute, render farms, and hybrid cloud/on-prem infrastructure
• Implement logging, monitoring, and performance profiling
• Ensure security, compliance, and data governance standards are upheld
• Partner with production, engineering, R&D, and operations teams
• Translate production pain points into technical solutions.
• Present findings, demos, and technical documentation to stakeholders
• Provide ongoing support during rollout and implementation.

• Design, prototype, and deploy end-to-end workflows supporting VFX, post-production, and emerging virtual production pipelines
• Integrate DCC applications (e.g., Nuke, Maya, Houdini) into automated and scalable systems
• Develop tools, APIs, and services that improve efficiency, quality, and cost
• Create proof-of-concept environments to simulate real production scenarios
• Document standards and best practices for operational adoption
• Evaluate, test, and integrate AI/ML models into production workflows
• Build and deploy ML pipelines (training, fine-tuning, inference,…