Lead Machine Learning Engineer (LLM)

The Walt Disney Company (Corporate); Buenos Aires; On-site; ARS 800,000 - 1,400,000; Full time

Job summary

La Walt Disney Company (Corporate) recherche un/une ingénieur ML expérimenté(e) pour diriger l’ingénierie LLM et l’orchestration RAG au sein de Disney Financial Insights (D-Fi). Vous piloterez la production et l’évolutivité des modèles, assurerez l’ingestion et l’organisation des documents financiers, et garantirez des résultats fiables et audités.

Vous travaillerez en anglais, avec un accent sur la rigueur technique et la conformité, afin de construire une plateforme AI robuste pour des données

Qualifications

• 6‑7+ années d'expérience en ML engineering avec NLP / systèmes de récupération.
• Anglais avancé.
• Diplôme en informatique/ingénierie; diplôme avancé un plus.
• Expérience pratique du fine‑tuning de modèles de base sur un domaine.
• Expérience avérée dans la construction et l'exploitation d'un système RAG en production.

Responsibilities

• Posséder le fine‑tuning et la personnalisation des LLM.
• Construire des jeux de données et des pipelines de fine‑tuning.
• Posséder l'architecture RAG de bout en bout.
• Concevoir et maintenir le vecteur DB, les embeddings, l'ingestion et la récupération.
• Concevoir et maintenir le catalogue de contexte.
• Construire la base de connaissances structurée des données financières.
• S'assurer que les sorties des modèles sont précises, fondées et auditées.
• Élaborer des cadres d'évaluation pour la fidélité et l'exactitude.

Skills

ML engineering

NLP

Retrieval systems

Applied LLM engineering

English fluency

Bachelor's degree en CS/Engineering

Fine-tuning foundation models

Production RAG systems

Evaluation frameworks

Finance process grounding

Education

Bachelor's in CS/Engineering

Tools

Pinecone

Weaviate

pgvector

Snowflake Cortex Search

PyTorch

Hugging Face Transformers

AWS

Azure

GCP

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.

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

• Own LLM fine‑tuning and model customization.
• Build training datasets, run fine‑tuning pipelines, and evaluate model performance on finance‑specific tasks — variance commentary generation, natural language query interpretation, and document intelligence.
• Own the RAG architecture end‑to‑end.
• Design and maintain the vector database, embedding strategy, document ingestion pipeline, and retrieval quality that determine how well the platform answers finance questions.
• Design and maintain the context catalog.
• Build the structured knowledge base of Disney financial data, policy rules, org hierarchy, and process documentation that grounds every agent and LLM response across the platform.
• Ensure model outputs are accurate, grounded, and auditable.
• Build the evaluation frameworks that measure groundedness and accuracy continuously.
• Own document intelligence quality.
• Ensure unstructured and semi‑structured finance documents are ingested, chunked, and retrieved in a way that produces reliable, traceable answers.

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

• 6‑7+ years of ML engineering experience, with demonstrated depth in NLP, retrieval systems, or applied LLM engineering.
• Advanced level of English (must).
• Bachelor's degree in Computer Science, Engineering, or related field; advanced degree a plus but not required.
• Hands‑on experience fine‑tuning foundation models for a specific domain, including building and curating training data.
• Track record of building and operating a production RAG system, not just experimenting with one.
• Comfort building rigorous evaluation frameworks for subjective, hard‑to‑measure outputs like generated commentary or natural language answers.
• Genuine curiosity about finance processes — you don't need a finance background, but grounding answers correctly requires learning the domain.

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

AI/LLM:

• Production experience fine‑tuning foundation models, including dataset construction, training pipeline design, and evaluation on domain‑specific tasks.
• Deep working knowledge of RAG architecture — embedding models, chunking strategy, retrieval quality tuning, and re‑ranking.
• Experience with vector databases/retrieval stores (e.g., Pinecone, Weaviate, pgvector, or Snowflake Cortex Search).
• Experience with major model providers and APIs (e.g., Anthropic Claude, OpenAI, or equivalent enterprise LLM platforms).
• Strong understanding of LLM evaluation methodology — groundedness/hallucination testing, human‑in‑the‑loop feedback systems, and regression testing for prompt/model changes.

Data & Databases:

• Strong data modeling background, including how to structure a context catalog or knowledge base for reliable retrieval.
• SQL fluency; comfort working with a modern cloud data warehouse (Snowflake preferred).
• Experience with document ingestion pipelines for unstructured or semi‑structured content.

Programming Languages & Engineering:

• Python fluency required — the primary language for fine‑tuning, RAG, and evaluation pipelines.
• Experience with ML training frameworks (e.g., PyTorch, Hugging Face Transformers) for fine‑tuning workflows.
• Familiarity with MLOps practices for versioning datasets, models, and evaluation results.
• Experience with cloud infrastructure (AWS, Azure, or GCP) at an architectural level.

Enterprise Systems (plus, not required):

• Exposure to ERP/EPM platforms such as SAP or Oracle EPM/Cognos, or experience grounding AI systems in enterprise 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