Senior AI Research Engineer

Job Posting Title:

Senior AI Research Engineer

Req ID:

10124362

Job Description:

About the Role & Team

“Any sufficiently complex technology is indistinguishable from magic.” - Arthur C. Clarke

At Imagineering, we are constantly exploring new ways to connect with our guests – to surprise them, make them smile, and open their minds to magic - not just in our parks and resorts, but everywhere around the world.

At Walt Disney Imagineering Research and Development, this "magic" emerges from the application of world-class technology and everything from new Guest-facing experiences to new tools for Imagineers and Cast Members who power our parks and bring that magic to life. Our team of engineers, designers, artists and scientists share a passion for solving impossible problems and building ground-breaking experiences.

At Disney Research Imagineering, we pursue and apply the science behind the magic: unlocking new opportunities for Imagineering in all aspects of project lifecycles, from early phase creative ideation to deployment.

The Role

We are seeking a Senior Research Engineer to design, prototype, and build software algorithms, components, and complex systems to support based on generative AI and intelligent agent concepts across Disney’s themed entertainment portfolio.

As a Senior AI research engineer, you will collaborate with cross-functional teams of researchers, engineers, and creatives. Your work will span exploratory proof-of-concepts, testing and evaluation, and the translation of experimental AI technologies into robust, production-ready tools.

You will report to the Associate Lab Director and contribute to the AI/ML applied research portfolio for Imagineering R&D.

What You Will Do

• Own all phases of the software design and implementation process for generative AI tools and intelligent agents, from early concept design, prototyping, detailed design, production deployment and testing.

• Apply cutting-edge agentic AI research to creative and technical tasks (e.g., visual synthesis, simulation, asset generation, design assistance).

• Evaluate agentic methods for feasibility, fidelity, controllability, and integration into WDI pipelines.

• Integrate AI models with APIs, databases, internal tools, and creative software.

• Lead internal design and code reviews and reviews

• Test and iterate on proof-of-concept designs, evolving requirements and designs

• Help teams manage free-form software and tool exploration when appropriate in early phases of projects, but understand when more structure is needed to progress to later phases of projects

• Deliver maintainable code in a dynamic fast paced development environment with rapidly changing requirements

• Troubleshoot and iterate on system performance and usability based on feedback from cross-disciplinary collaborators.

• Partner with interdisciplinary teams to ensure AI applications empower rather than constrain artistic and storytelling processes.

• Collaborate with internal and external research partners, including academic institutions, industry labs, and vendors.

• Translate scientific insights into working prototypes that bridge research and production-ready implementation.

• Mentor junior team members and contribute to the technical direction of AI initiatives within the lab.

• Contribute to the culture and community of WDI R&D with a positive and inspiring attitude

Required Qualifications & Skills

• 8+ years of professional software development experience

• Strong background in computer science fundamentals, design patterns, algorithms, and data structures

• Ability to design, communicate, and carry out software architecture using software development best practices

• Proficiency in multiple modern programming languages including Python, C/C++, C#, and Javascript

• Proficiency in machine learning libraries (e.g., PyTorch, TensorFlow), and large model libraries and APIs (e.g. OpenAI, Azure, Ollama, MCP, etc).

• A deep understanding of current large language and multimodal model agentic structures and capabilities, including their limitations.

• Demonstrated ability to bridge theoretical research with real-world implementation.

• Experience developing and maintaining generative models and AI agent architectures.

• Ability to work in a fast-paced, creative environment and adapt to rapidly changing requirements

• Experience with container orchestration tooling (Docker, Marathon)

• Experience with CI/CD and automation pipelines

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