Sr. Machine Learning Engineer (AI/ML Engineer)

The Walt Disney Company•Seattle, WA

2d•$148,700 - $199,400

About The Position

Department Description: At Disney, we’re storytellers. We make the impossible, possible. The Walt Disney Company (TWDC) is a world-class entertainment and technological leader. Walt’s passion was to continuously envision new ways to move audiences around the world—a passion that remains our touchstone in an enterprise that stretches from theme parks, resorts and a cruise line to sports, news, movies and a variety of other businesses. Uniting each endeavor is a commitment to creating and delivering unforgettable experiences — and we’re constantly looking for new ways to enhance these exciting experiences. The Enterprise Technology mission is to deliver technology solutions that align to business strategies while enabling enterprise efficiency and promoting cross-company collaborative innovation. Our group drives competitive advantage by enhancing our consumer experiences, enabling business growth, and advancing operational excellence. Team Description: The AI Engineering team builds ML solutions that enable creativity, personalization, and operational excellence across the company. You’ll be part of a team that values innovation, agility, and impact—where your work directly contributes to the future of entertainment. What You’ll Do: Work closely with Staff Engineers to design and engineer robust ML models and solutions. Design, create and deploy enhanced agents using agentic frameworks such as LangChain, LangGraph, ADK, strands, and other emerging technologies. Develop autonomous workflows where agents can reason, plan, use tools/APIs, collaborate, and self-correct to accomplish complex tasks. Engineer high-quality prompts and system instructions, including chain-of-thought orchestration, structured prompting, prompt templates, and dynamic prompt generation. Build and manage long-term and short-term memory for agents using vector databases, retrieval-augmented generation (RAG), and episodic memory techniques. Integrate agents with external tools, APIs, databases, and enterprise systems using function calling and tool execution frameworks. Build scalable platforms for conversational AI, automation, and personalized guest experiences. Drive strategy and best practices for prompt engineering, model fine-tuning, orchestration, and agent reliability. Implement observability and debugging for agentic systems, including tracing, step-level reasoning inspection, and failure analysis. Coach junior and mid-level engineers, fostering a culture of innovation and excellence. Partner with product, engineering, and research teams to define AI/agentic roadmaps and deliver business-impactful solutions. Ensure robust documentation and reproducibility across models, agents, and workflows. Set standards for safety, privacy, responsibility, and ethical use of AI/agents.

Requirements

5+ years industry experience in machine learning, generative AI, NLP, or agent development.
Skilled in Python and at least one ML library/framework (scikit-learn, TensorFlow, PyTorch).
Demonstrated experience designing, deploying, and maintaining LLMs and generative AI models.
Hands-on proficiency with at least one agentic development framework like LangChain, ADK, Strands, or equivalent.
Good understanding of different Agentic development patterns such as ReAct, Multi-agent etc.
Proven ability in designing and orchestrating agentic workflows and multi-agent systems.
Experience developing, deploying, and managing ML solutions on cloud platforms (AWS, GCP, Azure).
Strong collaborator and communicator experienced in leading cross-disciplinary teams.
Familiarity with responsible AI practices, compliance, and security requirements.
Git, Docker, CI/CD, and software best practices.

Nice To Haves

Experience integrating agent-based systems into consumer applications at scale.
Background in recommender systems, personalization, or conversational interfaces.
Solid understanding of reinforcement learning, RLHF, or related agent learning paradigms.
Experience with large-scale data pipelines and ML platform engineering.

Responsibilities

Work closely with Staff Engineers to design and engineer robust ML models and solutions.
Design, create and deploy enhanced agents using agentic frameworks such as LangChain, LangGraph, ADK, strands, and other emerging technologies.
Develop autonomous workflows where agents can reason, plan, use tools/APIs, collaborate, and self-correct to accomplish complex tasks.
Engineer high-quality prompts and system instructions, including chain-of-thought orchestration, structured prompting, prompt templates, and dynamic prompt generation.
Build and manage long-term and short-term memory for agents using vector databases, retrieval-augmented generation (RAG), and episodic memory techniques.
Integrate agents with external tools, APIs, databases, and enterprise systems using function calling and tool execution frameworks.
Build scalable platforms for conversational AI, automation, and personalized guest experiences.
Drive strategy and best practices for prompt engineering, model fine-tuning, orchestration, and agent reliability.
Implement observability and debugging for agentic systems, including tracing, step-level reasoning inspection, and failure analysis.
Coach junior and mid-level engineers, fostering a culture of innovation and excellence.
Partner with product, engineering, and research teams to define AI/agentic roadmaps and deliver business-impactful solutions.
Ensure robust documentation and reproducibility across models, agents, and workflows.
Set standards for safety, privacy, responsibility, and ethical use of AI/agents.