ML & Observability Engineer II

The Walt Disney Company (France); Glendale (CA); On-site; USD 118,000 - 158,000; Full time

Job summary

The Walt Disney Company in Glendale, CA is seeking a Software Engineer II to help build and operate ML-driven systems that enhance the reliability of Disney’s streaming ecosystem. You will work on production ML models that transform telemetry into automated detection and actionable insights across Disney+, Hulu, and ESPN.

You will participate in the ML lifecycle from feature engineering to GPU training and real-time inference, collaborating with platform teams to embed intelligence into

Qualifications

• 3+ years building ML-powered backends and RESTful APIs.
• Proficiency in Python and PyTorch/TensorFlow.
• Experience with ML experiments tracking (MLflow, Weights & Biases).
• Strong collaboration and communication across teams.

Responsibilities

• Contribute to production ML models for anomaly detection, including autoencoders, threshold models, and ensemble systems.
• Develop ML training pipelines using PyTorch on GPU clusters.
• Engineer features from time-series telemetry (latency, errors, infra metrics).
• Support real-time ML inference systems and alerting.
• Build AI-driven capabilities using foundation models for investigation and health signals.
• Create scalable APIs and services (FastAPI) delivering ML predictions and insights.

Skills

ML backend

Python

ML engineering

Collaboration

Education

Bachelor’s degree in Computer Science, ML, Statistics, Engineering, or equivalent

Tools

FastAPI

Flask

PyTorch

TensorFlow

MLflow

Weights & Biases

PySpark

Databricks

Docker

AWS/EKS

Job description

The Walt Disney Company in Glendale, CA is seeking a Software Engineer II to help build and operate ML-driven systems that enhance the reliability of Disney’s streaming ecosystem. You will work on production ML models that transform telemetry into automated detection and actionable insights across Disney+, Hulu, and ESPN.

You will participate in the ML lifecycle from feature engineering to GPU training and real-time inference, collaborating with platform teams to embed intelligence into