Sr Machine Learning Engineer

Design, build, and operate high-impact AI and machine learning systems for Disney Experiences Technology, with ownership across the AI/ML lifecycle.

Responsibilities

• Own the operational backbone of the AI/ML platform, including CI/CD pipelines, model and agent versioning, automated deployment, rollback, and release management to support reliable experimentation-to-production workflows.
• Build comprehensive observability and monitoring covering model and agent performance, drift, data quality, latency, cost, and reliability, with alerting and automated remediation where feasible.
• Develop production-scale AI systems, including multi-step agentic workflows and multi-agent orchestration platforms, and operationalize them end to end.
• Maintain full ownership of the AI/ML lifecycle, from implementation and testing through deployment and ongoing operational monitoring, delivering to schedule and specification.
• Design and implement Responsible AI frameworks, including hallucination detection, safety guardrails, evaluation systems, and observability for reliable and accurate deployment.
• Establish evaluation frameworks for Large Language Models and agent-based systems, measuring model quality, task success rates, safety compliance, and operational effectiveness.
• Apply LLMOps and MLOps best practices across the platform, including infrastructure-as-code, reproducibility, automated testing, and environment parity.
• Partner with cross-functional teams such as product managers, data scientists, application teams, vendors, and partners to align on requirements, iterate on solutions, and deliver outcomes.
• Provide hands-on technical leadership by driving architectural decisions across AI development, LLMOps, quality assurance, and production deployment.
• Identify and resolve technical blockers that could impact timelines or deliverables.
• Communicate technical strategy and progress to executive leadership and key stakeholders.
• Work directly on high-complexity engineering problems to maintain project velocity and quality.
• Conduct research and experimentation with emerging AI technologies and frameworks, evaluating and integrating capabilities that advance the platform.

Requirements

• 5+ years of experience designing, building, and deploying AI/ML solutions at scale, including 1–2 years of production experience with Generative AI technologies.
• Hands-on MLOps/LLMOps expertise implementing CI/CD pipelines, monitoring for models and agents, versioning, observability, and production lifecycle management.
• Experience deploying to major cloud platforms (AWS, Azure, or GCP), with demonstrated ability to architect, scale, and operate cloud-native ML solutions.
• Expert-level Python programming and experience across AI/ML development ecosystems.
• Strong machine learning foundation, including statistical modeling plus supervised and unsupervised learning algorithms.
• Advanced prompt engineering skills with knowledge of optimization techniques and LLM interaction best practices.
• Broad ML capabilities covering traditional methods (classification, regression, clustering) and deep learning approaches.
• Production-grade Generative AI experience deploying and maintaining LLMs and multi-modal models in live environments.
• Strong analytical and problem-solving skills in complex and rapidly evolving environments.
• Excellent communication and collaboration skills, translating complex technical concepts for diverse audiences and driving cross-functional alignment.
• Track record of partnering across organizational levels, from individual contributors to senior leadership.
• Ability to influence and lead in matrix organizations through relationship-building and collaboration.

About the Role & Team

• The DXT AI Technology Platform team builds an AI enablement platform for the DX segment, providing streamlined AI and Generative AI capabilities to build solutions on top of the platform.
• This Senior Machine Learning Engineer role will design, develop, and implement enterprise-grade AI/ML solutions, including agentic systems, multi-modal models, RAG, and Responsible AI applications.

Technologies

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

Preferred Qualifications

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

Required Education

• Bachelor's degree in Computer Science, Machine Learning, Mathematical Sciences, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.

Preferred Education

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

Location: Orlando, FL (onsite)

Compensation: USD 137,200 - 184,000 per year