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Lead Machine Learning Engineer

Job in Orlando, Orange County, Florida, 32885, USA
Listing for: The Walt Disney Company (France)
Full Time position
Listed on 2026-01-20
Job specializations:
  • IT/Tech
    AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below

At Disney Experiences Technology, our team creates world-class immersive and digital experiences for the Company’s vacation brands, Disney’s Parks and 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 My Disney Experience  app and Hey, Disney!

The team is seeking a results-oriented and hands-on Lead 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 lead complex, cross-functional projects with a strong emphasis on reuse, scalability, reliability, and performance.

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

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 Lead 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.

This position is in office.

What You’ll Do:
  • Develop sophisticated, production-scale AI systems, including multi-step agentic workflows and multi-agent orchestration platforms.
  • Build tools & agents with advanced capabilities in reasoning, planning, and adaptive tool utilization to address complex business challenges.
  • Drive complete ownership of the AI/ML lifecycle – encompassing implementation, comprehensive testing, deployment, and continuous operational monitoring – delivering projects on schedule and to specification.
  • Produce high-quality, maintainable code for model training pipelines, evaluation frameworks, and inference services that meet production standards.
  • Partner strategically with cross-functional stakeholders including product leaders, 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 and championing best practices across AI development, LLMOps, quality assurance, and production deployment.
  • Design and implement responsible AI frameworks including hallucination detection, safety guardrails, comprehensive evaluation systems, and observability infrastructure to ensure model reliability, accuracy, and ethical deployment.
  • Establish comprehensive evaluation frameworks for Large Language Models and agent-based systems, measuring model quality, task success rates, safety compliance, and operational effectiveness.
  • Proactively identify and resolve technical blockers that could impact project timelines or deliverables.
  • Communicate technical strategy and progress to executive leadership and key stakeholders with clarity and confidence.
  • Engage directly in development and problem‑solving, particularly on high‑complexity technical challenges, to maintain project velocity and quality.
  • Drive innovation through research and experimentation with emerging AI technologies and frameworks, evaluating and integrating new capabilities that advance our platform.
Basic Qualifications:
  • 7+ years of proven expertise in designing, building, and deploying AI/ML solutions at scale, with 1-2 years of production experience in Generative AI technologies.
  • Strong foundation in machine learning including statistical modeling, supervised and unsupervised learning algorithms.
  • Advanced skills in prompt engineering with deep understanding of optimization techniques and best practices for LLM interactions.
  • Expert‑level programming proficiency in Python and AI/ML development ecosystems.
  • Deep expertise in modern AI frameworks including LLM application development and agentic systems (Lang Chain, CrewAI, or similar).
  • Comprehensive MLOps experience with…
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