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Senior Machine Learning Engineer
The Walt Disney CompanySenior Machine Learning Engineer at Disney, responsible for designing and implementing self-healing infrastructure management systems. Collaborating across teams to enhance operational excellence.
Posted 4/15/2026full-timeLake Buena Vista • California, Florida, Washington • 🇺🇸 United StatesSenior💰 $155,700 - $218,700 per yearWebsite
Tech Stack
Tools & technologiesCloudDockerGoJavaScriptKubernetesPythonPyTorchRustScikit-LearnTensorflowTypeScript
About the role
Key responsibilities & impact- Work alongside our first-class applications, infrastructure & operations teams to understand current manual processes and business requirements
- Architect, design, and implement reusable machine learning frameworks, patterns, and services that integrate into the enterprise automation and observability platforms
- Design, train, and deploy machine learning models for anomaly detection, forecasting, predictive analytics, event correlation, pattern recognition, classification, causal analysis, and more in distributed environments
- Build near-real-time inference pipelines that generate actionable insights from live telemetry
- Analyze incident and historical data to uncover leading indicators and predictive signals
- Collaborate with cross-functional teams including network engineers, software developers, machine learning engineers, and operations teams
Requirements
What you’ll need- 7+ years of software engineering experience, with expertise in automation, machine learning, and AI technologies
- Proven hands-on experience building production-grade ML models and inference pipelines
- Strong proficiency with modern ML frameworks such as PyTorch, TensorFlow, Scikit-learn, etc.
- Proven hands-on experience using software to build frontend, APIs and backend functionality; strong proficiency with Python, JavaScript, TypeScript, Go, or Rust
- Strong hands-on experience building and deploying event-driven or streaming data, machine learning models in production
- Solid foundation in statistics, data analysis, and applied machine learning techniques
- Experience with modern cloud platforms, container orchestration (Kubernetes/Docker), identity/auth frameworks, data and workflow orchestration.
- Experience operationalizing models in distributed, production environments
- Experience working with large-scale, real-world datasets (noisy, incomplete, non-standardized, and evolving)
Benefits
Comp & perks- A bonus and/or long-term incentive units may be provided as part of the compensation package,
- Full range of medical, financial, and/or other benefits