Lead Machine Learning Engineer (ML Ops)

The Walt Disney Company (Corporate); Buenos Aires; On-site; ARS 3,000,000 - 5,000,000; Full time

Job summary

La Walt Disney Company, au sein de Disney Argentina, cherche un Lead ML Ops pour concevoir, déployer et maintenir des systèmes ML en production. Vous piloterez l'infrastructure ML, les pipelines de réentraînement et le registre des modèles, tout en assurant sécurité et conformité dans un contexte financier.

Le candidat idéal dispose d'au moins 7 ans d'expérience en ML/plateforme, maîtrise Python et outils ML, et sait opérer dans un cadre réglementé.

Qualifications

• 7+ années d'expérience en ML ou ingénierie de plateforme, avec une forte expertise ML Ops et systèmes ML en production.
• Bachelor's degree en informatique/ingénierie; diplôme avancé apprécié mais non obligatoire.
• Niveau d'anglais avancé.
• Expérience démontrée en construction de systèmes de surveillance, d'alerting et de rollback pour modèles ML en production.
• Expérience avec un registre de modèles, un feature store ou un système de tracking d'expérimentations à grande échelle.
• Confort dans un environnement réglementé avec traçabilité et auditabilité.
• Idéal si vous avez soutenu d'autres ingénieurs ML en production; ce rôle est la colonne vertébrale de fiabilité de l'équipe.

Responsibilities

• Concevoir, écrire et déployer du code productionnel pour les pipelines ML et l'infrastructure ML.
• Assurer la productionnalisation des modèles et des agents, packaging, versioning et déploiement à grande échelle.
• Gérer les pipelines de réentraînement, maintenir le catalogue des caractéristiques et le registre de modèles.
• Mettre en place et maintenir la surveillance, les alertes et les procédures de rollback.
• Garantir la sécurité, la conformité et l'auditabilité des systèmes ML dans un cadre d'entreprise.

Skills

ML Ops

Python

Docker

Kubernetes

CI/CD

MLflow

Weights & Biases

Monitoring & alerting

Snowflake

SQL

Cloud: AWS/GCP/Azure

Education

Bachelor's degree in Computer Science/Engineering

Tools

MLflow

Weights & Biases

Docker

Kubernetes

Snowflake

SQL

Airflow

Terraform

Job description

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 model metrics. Familiarity with the operational characteristics of RAG and agentic systems in production (latency, cost, failure modes).

Data & Databases:

Strong understanding of data pipelines feeding ML systems, including how stale or low-quality data manifests as model degradation. SQL fluency; comfort working with a modern cloud data warehouse (Snowflake preferred).

Programming Languages & Engineering:

Python fluency required — the primary language across the ML platform. Strong MLOps tooling experience — model registries, feature stores, experiment tracking (e.g., MLflow, Weights & Biases, or equivalent). Containerization and orchestration experience (Docker/Kubernetes) for serving models and agents reliably at scale. CI/CD experience for ML systems, including automated retraining and deployment pipelines. Experience with cloud infrastructure (AWS, Azure, or GCP), including monitoring and alerting tooling.

Enterprise Systems (plus, not required):

Experience meeting security, compliance, or audit requirements for AI/ML systems in a regulated or enterprise environment, particularly around financial data.

Additional Information:

At Disney, we believe it takes great people to create the memorable experiences, products and services our consumers know and love. We are a team of storytellers and hire under equal opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, disability and gender identity. We foster a corporate culture of belonging and inclusiveness, which empowers our staff and company to thrive. At Disney, everyone has the opportunity to speak up and participate, grow and share ideas.

“You can design and create, and build the most wonderful place in the world. But it takes people to make the dream a reality.” Walt Disney

Disclaimer

This position is with TWDC Argentina S.A., which is part of a business we call The Walt Disney Company (Corporate).

To learn more about Disney's guidelines on the use of AI for candidates,

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