Sr Machine Learning Engineer

Walt Disney Attractions Technology LLC is building an enterprise AI enablement platform for Disney Experiences Technology, aimed at providing streamlined AI and Generative AI capabilities across the DX segment. In this onsite role in Orlando, FL, you will design, develop, and deploy high-impact AI/ML solutions, including agentic systems, multi-modal models, and Responsible AI applications, while taking end-to-end ownership of the AI/ML lifecycle.

About the role

The DXT AI Technology Platform team focuses on creating a platform that lets teams build solutions around and on top of robust AI and Generative AI capabilities. The Senior Machine Learning Engineer will own implementation through production operations, covering LLMOps/MLOps, evaluation, CI/CD, observability, and responsible deployment practices.

Responsibilities

• Own the operational backbone of the AI/ML platform by designing and running CI/CD pipelines, managing model and agent versioning, automated deployment, rollback, and release management.
• Build comprehensive observability and monitoring for model and agent performance, drift, data quality, latency, cost, and reliability, including 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, covering implementation, testing, deployment, and continuous operational monitoring to deliver projects on schedule and to specification.
• Design and implement Responsible AI frameworks, including hallucination detection, safety guardrails, evaluation systems, and observability to support reliable, accurate, and ethical deployment.
• Establish evaluation frameworks for Large Language Models and agent-based systems, including measures for model quality, task success rates, safety compliance, and operational effectiveness.
• Champion LLMOps and MLOps best practices, including infrastructure-as-code, reproducibility, automated testing, and environment parity across the platform.
• Partner with cross-functional stakeholders including product managers, data scientists, application teams, vendors, and partners to align on requirements and iterate toward successful outcomes.
• Provide hands-on technical leadership by driving architectural decisions across AI development, LLMOps, quality assurance, and production deployment.
• Proactively identify and resolve technical blockers that could affect 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 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 capabilities that strengthen the platform.

Requirements

• 5+ years of proven expertise designing, building, and deploying AI/ML solutions at scale, including 1–2 years of production experience in Generative AI technologies.
• Comprehensive MLOps/LLMOps experience with hands-on implementation of CI/CD pipelines, model and agent monitoring, versioning, observability, and lifecycle management in production.
• Production deployment experience on AWS, Azure, or GCP, with demonstrated ability to architect, scale, and operate cloud-native ML solutions.
• Expert-level programming proficiency in Python and AI/ML development ecosystems.
• Strong foundation in machine learning, including statistical modeling and supervised and unsupervised learning algorithms.
• Advanced prompt engineering skills with a deep understanding of optimization techniques and best practices for LLM interactions.
• Versatile ML background spanning traditional techniques (classification, regression, clustering) and deep learning approaches.
• Production-grade Generative AI experience deploying and maintaining LLMs and multi-modal models in live environments.
• Exceptional analytical capabilities with a record of solving complex technical problems in ambiguous, fast-changing contexts.
• Outstanding communication and collaboration skills to translate complex technical concepts for diverse audiences and drive cross-functional alignment.
• Success partnering across organizational levels, from individual contributors to senior leadership.
• Proven ability to influence and lead in matrix organizations through collaboration and relationship-building.

Technologies

• Python
• AWS, Azure, GCP
• CI/CD
• LLMOps, MLOps
• Infrastructure-as-code
• Docker, Kubernetes, Terraform

Location and compensation

• Location: Orlando, FL (onsite)
• Salary: USD 137,200 - 184,000 per yearly

Education

• Bachelor's degree in Computer Science, Machine Learning, Mathematical Sciences, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field, and/or equivalent work experience.
• Preferred: Master's degree or Ph.D in Artificial Intelligence, Machine Learning, Mathematical Sciences, Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or a comparable field, and/or equivalent work experience.

Preferred qualifications

• Experience with container orchestration and infrastructure-as-code (Docker, Kubernetes, Terraform) for ML workloads.
• Experience with vector databases and embedding technologies.