Associate Machine Learning Engineer

The Walt Disney Company • Seattle, WA

5d

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: Implement, test, and deploy machine learning solutions, including generative models (e.g., GANs, LLMs) and intelligent agents. Assist in the creation and ongoing maintenance of agents using agentic frameworks (e.g. LangChain, ADK, Strands) for conversational and task automation applications. Fine-tune and evaluate large language models (LLMs) and dialog/conversational systems. Prepare and clean datasets for AI/ML analysis, including natural language processing (NLP) using synthetic data generation. Collaborate across product, engineering, and data science teams to collect requirements and deliver innovative agentic and generative AI projects. Conduct research, experimentation, and evaluation of new generative AI models and agent framework capabilities. Monitor, troubleshoot, and continuously improve deployed agents for performance, reliability, and safety. Document workflows, models, and agent architectures to ensure reproducibility and transparency. Stay current on advances in generative AI, LLMs, and agent framework technology.

Requirements

• Programming experience in Python and standard ML libraries (scikit-learn, TensorFlow, PyTorch).
• Understanding of fundamental machine learning concepts, generative models, NLP, and LLMs.
• Knowledge of or hands-on experience with agentic frameworks such as LangChain, ADK (Agent Development Kit), Strands, or similar.
• Familiarity with agent design patterns, prompt engineering, model fine-tuning, and orchestration tools.
• Experience with data analysis and preprocessing libraries (pandas, NumPy).
• Familiarity with version control systems (e.g., Git).
• Strong communication, collaboration, and documentation skills.
• Eagerness to learn and grow in dynamic settings.

Nice To Haves

• Internship or project experience with generative AI, LLMs, and agent development.
• Exposure to deploying agent-based systems on cloud platforms (AWS, GCP, Azure).
• Experience with data visualization tools (matplotlib, Tableau).
• Understanding of software engineering principles and best practices.

Responsibilities

• Implement, test, and deploy machine learning solutions, including generative models (e.g., GANs, LLMs) and intelligent agents.
• Assist in the creation and ongoing maintenance of agents using agentic frameworks (e.g. LangChain, ADK, Strands) for conversational and task automation applications.
• Fine-tune and evaluate large language models (LLMs) and dialog/conversational systems.
• Prepare and clean datasets for AI/ML analysis, including natural language processing (NLP) using synthetic data generation.
• Collaborate across product, engineering, and data science teams to collect requirements and deliver innovative agentic and generative AI projects.
• Conduct research, experimentation, and evaluation of new generative AI models and agent framework capabilities.
• Monitor, troubleshoot, and continuously improve deployed agents for performance, reliability, and safety.
• Document workflows, models, and agent architectures to ensure reproducibility and transparency.
• Stay current on advances in generative AI, LLMs, and agent framework technology.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level