Résumé du poste:

Job Requirements

BUILD SOMETHING BIGGER THAN YOURSELF

The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: Disney Entertainment, ESPN, Disney Parks, and Experiences and Products. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.

How you will contribute to our magical experience?

Disney Financial Insights (D-Fi) is a new platform reimagining how Finance teams and budget owners across Disney interact with financial data — replacing manual pulls, static reports, and email-driven approvals with one AI-powered, orchestrated experience built on top of Disney financial systems.

We're hiring the founding engineering team for this AI framework. One theme unifies every engineering role on D-Fi: autonomy and trust. You make autonomous decisions durable — turning models and agents built by others into reliable, monitored, production systems Disney can depend on every day. You'll own model productionalization, operational reliability, and the ML infrastructure layer — taking models and agents from development into production, keeping them current as Disney's data and processes evolve,



and making sure the platform meets Disney's security, compliance, and audit standards for AI handling financial data.

Owns model productionalization, operational reliability, and the ML infrastructure layer. Responsible for taking models and agents built by ML Engineers from development into production — packaging, serving, versioning, and deploying them reliably at scale. Builds and maintains automated retraining pipelines that keep models current as Disney's financial data, org structure, and business processes evolve. Owns model monitoring infrastructure: drift detection, performance degradation alerting, and rollback procedures when a model regresses. Manages the feature store, model registry, and experiment tracking infrastructure. Ensures the ML platform meets Disney's security, compliance, and audit requirements for AI systems handling financial data.

The Lead Machine Learning Engineer (ML Ops) will be responsible for:

Own model productionalization. Take models and agents built by other ML engineers from development into production — packaging, serving, versioning, and deploying them reliably at scale. Build automated retraining pipelines. Keep models current as Disney's financial data, org structure, and business processes evolve, without manual reintervention each time. Own model monitoring infrastructure.



Build drift detection, performance degradation alerting, and rollback procedures so a regressed model is caught and corrected quickly. Manage the ML platform's operational backbone. Own the feature store, model registry, and experiment tracking infrastructure the rest of the ML team relies on. Ensure compliance and auditability by design. Meet Disney's security, compliance, and audit requirements for AI systems handling financial data, from day one of any new model going into production.

What we need from you to be part of this story:

7+ years of ML or platform engineering experience, with a strong track record in ML Ops and production ML systems. Bachelor's degree in Computer Science, Engineering, or related field; advanced degree a plus but not required. Advanced level of English (must). Demonstrated experience building monitoring, alerting, and rollback systems for production ML models, not just training them. Experience building or operating a model registry, feature store, or experiment tracking platform at scale. Comfort operating in a regulated or compliance-sensitive environment, with rigor around auditability and traceability. Background supporting other ML engineers' models in production is a strong plus — this role is the reliability backbone for the rest of the ML team.

You'll be architecting, designing and writing production code.

AI/LLM:

Working knowledge of LLM and agentic system architecture sufficient to productionize models and agents built by teammates. Understanding of LLM evaluation methodology, including how to detect regression or drift in generated outputs, not just numeric mo

📌 Lead Machine Learning Engineer (Buenos Aires)
🏢 The Walt Disney Company (Corporate)
📍 Buenos Aires