Manager, AI/ML Engineering

Universal Orlando•Orlando, FL

About The Position

At UDX’s Global Technology & Innovation, we support our global parks by providing the data, advanced analytics, and technology needed to create extraordinary experiences. By knowing our guests’ hearts and minds, we deliver relevant, bespoke moments throughout the Universal journey ensuring a vacation experience like no other. The Manager, AI/ML Engineering will lead a team of AI/ML engineers to design and deploy enterprise-scale AI solutions that drive measurable business outcomes. This role is a hands-on leadership position, guiding the team to deliver production-ready systems that enhance business performance and customer experiences. Key responsibilities include managing a portfolio of applied AI/ML initiatives, translating strategy into execution, embedding responsible AI practices, and fostering a culture of innovation. The ideal candidate will be a collaborative leader, committed to developing talent, championing technical rigor, and enabling innovation at scale across the organization.

Requirements

7+ years experience in applied‑AI, data science or software‑engineering roles
2+ years managing technical teams delivering end‑to‑end AI/ML products in production is preferred; or equivalent combination of education and experience.
Deep expertise in modern ML/AI frameworks (e.g., PyTorch, TensorFlow, LangChain) and cloud AI services (AWS, GCP, or Azure).
GenAI Model Fluency: Demonstrated expertise with the current landscape of foundation models (instruction-tuned, code, vision, speech, multi-modal) and their tooling stacks.
Experience with Retrieval‑Augmented Generation (RAG), vector databases, and prompt‑engineering best practices.
Familiarity with cost‑optimization for AI workloads.
Leadership Acumen: Proven ability to motivate, coach, and retain high‑performing talent while driving cross‑functional alignment and decision‑making.
Strategic & Business Orientation: Track record of connecting technical solutions to tangible business value and managing a portfolio of initiatives.
Communication Excellence: Skilled storyteller comfortable presenting to executives and mentoring both technical and non‑technical audiences.
Responsible‑AI Literacy: Hands‑on experience applying privacy, security, fairness, and compliance principles in production AI systems.
Project Management: Knowledge of Agile/Scrum or Kanban methodologies, with demonstrated success in fast‑paced, ambiguous environments.

Nice To Haves

Master’s degree in Computer Science, Engineering, Data Science or in a relevant applied quantitative field is preferred.

Responsibilities

Lead and mentor a team of AI/ML engineers, promoting collaboration, continuous learning, and high-impact delivery.
Recruit, develop, and retain a high-performing AI development team by setting clear goals, providing regular coaching and feedback, and fostering a culture of innovation and experimentation.
Create individualized growth plans to advance team members' technical depth and leadership capabilities.
Oversee team performance, ensuring alignment with business goals and timely execution of key initiatives.
Manage project timelines, prioritize resources effectively, and ensure delivery within scope and schedule.
Facilitate monthly, quarterly, and annual planning to align team objectives with broader enterprise strategies.
Oversee AI/ML development, code quality, and product‑lifecycle best practices in AI/ML to ensure scalable, maintainable, and secure solutions in production.
Engage with internal/external partners to gather requirements and collaborate with technology engineers, architects and business stakeholders to help in designing a robust solution.
Remove roadblocks, manage sprint ceremonies, and track velocity, quality, and reliability KPIs.
Establish governance for product monitoring, drift detection, and incident response.
Help define the strategy for AI products, balancing near‑term deliverables with long‑term platform evolution.
Stay abreast of the rapidly evolving GenAI ecosystem. Systematically compare open-source and commercial large-language-model families across benchmarks, licensing terms, latency/cost profiles, and safety features; generate data-driven recommendations on which models to adopt, fine-tune, or replace.
Partner with Product, Infrastructure, Architecture, Security, and Legal teams to align on scope, timelines, and responsible‑AI requirements.
Communicate complex technical concepts and program status to senior leadership, championing the value of AI initiatives.
Understands and actively participates in Environmental, Health & Safety responsibilities by following established UO policy, procedures, training and team member involvement activities.
Performs other duties as assigned.