This role pays less than
60%
of similar roles. Most pay
$122,661–$169,050
— the shaded band above.
At the midpoint, this role pays about
$138k
versus about
$146k
for comparable roles.
Based on 240 similar postings.
Employer
About The Walt Disney Company
The Walt Disney Company is a diversified global entertainment and media enterprise operating in segments including Disney Parks, Experiences and Products; Entertainment (ABC, Hulu, Disney+); and ESPN. Industry: Entertainment & Media
The Walt Disney Company currently has
118 open roles
on FindRole.
Listed pay typically runs
$148,700–$199,400
across 118 roles with salary data.
As a Software Engineer II within the Observability & Insights group, you will build and operate machine learning models and AI-driven systems to enhance the reliability of Disney’s streaming ecosystem. You will develop production ML models for anomaly detection, including autoencoders and statistical threshold systems, while managing the full ML lifecycle from feature engineering on time-series data to training on GPU clusters. Your daily work involves building real-time inference pipelines, developing FastAPI services, and integrating foundation models like Claude and GPT-4 for automated investigation of system health signals. You will utilize a technical stack including Python, PyTorch, TensorFlow, MLflow, Spark, Databricks, and Docker. This role solves complex problems regarding distributed system performance and reliability across platforms such as Disney+, Hulu, and ESPN by transforming telemetry data into proactive insights and automated detection tools.
What does a Software Engineer earn in California?
Median $214000 from 775 postings across 63 companies.
Develop and maintain production ML models for anomaly detection using autoencoders and statistical threshold systems.
Build and improve ML training pipelines using PyTorch on GPU clusters, including feature engineering and model deployment via MLflow.
Engineer features from time-series telemetry data such as error ratios, latency, and infrastructure metrics.
Support real-time ML inference systems for prediction cycles, detection logic, and automated alert generation.
Build AI-driven capabilities using foundation models like Claude or GPT-4 for automated system health investigation.
Create and deploy scalable APIs and services using FastAPI to deliver ML predictions and insights to internal tools.
Improve model performance through continuous evaluation, retraining, and threshold tuning.
What we're looking for
Bachelor’s degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent experience.
3+ years of professional software engineering experience building and maintaining ML-powered backends, data-driven microservices, and RESTful APIs using FastAPI or Flask.
Strong hands-on experience in end-to-end ML engineering using PyTorch or TensorFlow for model architecture, feature engineering, training, and evaluation.
Proficiency in Python and at least one ML framework (PyTorch preferred).
Experience managing model experiments, lineage, and hyperparameter tracking using tools like MLflow or Weights & Measures.
Practical experience processing and querying large-scale telemetry or time-series datasets using PySpark, Pandas, or Databricks.
Experience with version control (GitHub), containerization (Docker), and cloud-native deployments (AWS/EKS).
Experience with foundation model integration, prompt engineering, RAG architectures, or orchestration frameworks like LangChain or LangGraph (preferred).