Sr Machine Learning Engineer

The Senior Machine Learning Engineer will design, build, and deploy high-impact AI and ML solutions, while helping establish an enterprise AI enablement platform for Disney Experiences Technology. The role includes end-to-end ownership of the AI/ML lifecycle across LLMOps and MLOps, with a focus on production reliability, responsible deployment, and measurable evaluation.

Key Responsibilities

• Own the operational backbone of the AI/ML platform, including CI/CD pipeline design and execution, model and agent versioning, automated deployment, rollback, and release management from experimentation to production.
• Build and operate 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 full ownership of the AI/ML lifecycle across 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 and ethical model deployment.
• Establish evaluation frameworks for large language models and agent-based systems, tracking model quality, task success rates, safety compliance, and operational effectiveness.
• Apply LLMOps and MLOps best practices through infrastructure-as-code, reproducibility, automated testing, and environment parity across the platform.
• Collaborate with 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 influencing architectural decisions across AI development, LLMOps, quality assurance, and production deployment.
• Identify and resolve technical blockers that could affect timelines or deliverables.
• Communicate technical strategy and progress to executive leadership and key stakeholders with clarity and confidence.
• Participate directly in development and problem-solving for high-complexity technical challenges to maintain delivery velocity and quality.
• Advance the platform through research and experimentation with emerging AI technologies and frameworks, evaluating and integrating new capabilities.

Required Qualifications

• 5+ years of proven experience designing, building, and deploying AI/ML solutions at scale, including 1–2 years of production experience in Generative AI technologies.
• Hands-on MLOps/LLMOps experience implementing CI/CD pipelines, model and agent monitoring, versioning, observability, and production lifecycle management.
• 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 machine learning foundation, including statistical modeling as well as supervised and unsupervised learning.
• Advanced prompt engineering skills with an understanding of optimization techniques and LLM interaction best practices.
• Broad ML capability covering traditional approaches (classification, regression, clustering) and deep learning.
• Production-grade Generative AI experience deploying and maintaining LLMs and multi-modal models in live environments.
• Exceptional analytical skills and experience solving complex technical problems in ambiguous, fast-changing environments.
• Strong communication and collaboration abilities, including translating complex technical concepts for diverse audiences and aligning cross-functionally.
• Demonstrated success partnering across organizational levels, from individual contributors to senior leadership.
• Proven ability to influence and lead in matrix organizations through effective relationship-building and collaboration.

Technologies

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

About the Role and Team

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

Preferred Qualifications

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

Education

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

Location and Compensation

Location: Orlando, FL (onsite)

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

Experience Level: 5+ years