Sr Machine Learning Engineer

Job Summary: 

At Disney Experiences Technology, our team creates world-class immersive digital experiences for the Company’s premier vacation brands including Disney’s Parks & Resorts worldwide, Disney Cruise Line, Aulani, A Disney Resort & Spa, and Disney Vacation Club. The Disney Experiences Technology team is responsible for the end-to-end digital and physical Guest experience for all technology & digital-led initiatives across the Attractions & Entertainment, Food & Beverage, Resorts & Transportation, and Merchandise lines of business as well as other initiatives including the MyDisneyExperience app and Hey, Disney! 

The team is seeking a results-oriented and hands-on Senior Machine Learning Engineer to design, develop, and deploy high-impact AI/ML solutions that drive measurable business value across our entertainment company. In this role, you will Senior complex, cross-functional projects with a strong emphasis on reuse, scalability, reliability, and performance.  

The Senior ML Engineer will report to the ML Engineering Manager. 

This position is in office. 

About The Role & Team: 

The DXT AI Technology Platform team is responsible for building an AI enablement platform for the DX segment that provides streamlined AI & Generative AI capabilities for the segment to build solutions around and on top of.  The Senior Machine Learning Engineer will design, develop, implement enterprise grade and robust AI/ML solutions, including agentic systems, multi-modal models, RAG, and Responsible AI applications. 

What You'll Do: 

• Own the operational backbone of the AI/ML platform — design and run the CI/CD pipelines, model/agent versioning, automated deployment, rollback, and release management that move systems from experimentation to production reliably and repeatably. 

• Stand up comprehensive observability and monitoring infrastructure — model/agent performance, drift, data quality, latency, cost, and reliability — with alerting and automated remediation where possible. 

• Develop production-scale AI systems, including multi-step agentic workflows and multi-agent orchestration platforms, and operationalize them end to end. 

• Drive complete ownership of the AI/ML lifecycle — implementation, testing, deployment, and continuous operational monitoring — delivering projects on schedule and to specification. 

• Design and implement Responsible AI frameworks — hallucination detection, safety guardrails, evaluation systems, and observability — to ensure model reliability, accuracy, and ethical deployment. 

• Establish evaluation frameworks for Large Language Models and agent-based systems, measuring model quality, task success rates, safety compliance, and operational effectiveness. 

• Champion LLMOps and MLOps best practices — infrastructure-as-code, reproducibility, automated testing, and environment parity — across the platform. 

• Partner strategically with cross-functional stakeholders including product managers, data scientists, application teams, vendors, and partners to align on requirements, iterate on solutions, and deliver successful outcomes. 

• Provide hands-on technical leadership, driving architectural decisions acr