Software Engineer II – ML, Observability

The Walt Disney Company

. Contribute to production ML models for anomaly detection, including autoencoders, statistical threshold models, and ensemble detection systems .

Posted 10/7/2026full-timeUnited StatesMid-LevelSenior💰 $117,500 - $165,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining ML-powered backends and data-driven microservices, with a strong focus on end-to-end ML engineering using frameworks like PyTorch and TensorFlow. Proficient in deploying scalable services and collaborating cross-functionally to integrate ML intelligence into workflows.

Highest-signal resume keywords

ML Model DevelopmentPyTorch or TensorFlow ProficiencyFastAPI or Flask ExperienceData Processing with PySpark or PandasModel Experiment Management with MLflow

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning EngineeringFeature EngineeringModel EvaluationHyperparameter TrackingData TransformationRESTful API DevelopmentAnomaly DetectionStatistical Threshold ModelsEnsemble Detection SystemsAutoencoders

Soft Skills

Analytical SkillsTroubleshooting SkillsCollaboration SkillsCommunication Skills

Tools & Technologies

PyTorchTensorFlowFastAPIFlaskMLflowWeights & BiasesGitHubDockerAWS/EKSDatabricks

Certifications & Qualifications

Bachelor's Degree in Computer ScienceMachine LearningStatisticsEngineering

Industry Keywords

Telemetry DataTime-Series DatasetsFoundation Model IntegrationPrompt EngineeringRAG ArchitecturesLangChainLangGraphDatadogGrafanaHigh-Volume Telemetry

Tech Stack

Tools & technologies

AWSCloudDockerFlaskGrafanaMicroservicesPandasPySparkPythonPyTorchSparkTensorflow

About the role

Key responsibilities & impact

Contribute to production ML models for anomaly detection, including autoencoders, statistical threshold models, and ensemble detection systems
Develop and improve ML training pipelines using PyTorch on GPU clusters
Perform feature engineering on time-series telemetry, including windowing, normalization, and data quality safeguards
Support real-time ML inference systems, including model serving, detection logic, and alert generation
Build AI-driven capabilities using Claude and GPT-4 for automated investigation and reasoning over system health signals
Create and deploy scalable FastAPI services delivering ML predictions, health status, and insights
Partner cross-functionally to embed ML intelligence into incident response and release validation workflows
Contribute to model evaluation, retraining, threshold tuning, model design, code reviews, and end-to-end feature delivery

Requirements

What you’ll need

3+ years of professional software engineering experience building, scaling, and maintaining ML-powered backends, data-driven microservices, and production RESTful APIs using FastAPI or Flask
Strong hands-on experience in end-to-end ML engineering using PyTorch or TensorFlow, including model architecture selection, feature engineering, training, and evaluation
Proficiency in Python and at least one ML framework
Experience managing model experiments, lineage, and hyperparameter tracking using MLflow or Weights & Biases
Experience processing, transforming, and querying large-scale telemetry, event, or time-series datasets using PySpark, Pandas, or Databricks
Experience with GitHub, Docker, and cloud-native deployments using AWS/EKS
Strong analytical and troubleshooting skills
Strong collaboration and communication skills, with the ability to work cross-functionally
Bachelor's degree in Computer Science, Machine Learning, Statistics, Engineering, or equivalent experience
Preferred: experience with foundation model integration, prompt engineering/evaluation, RAG architectures, LangChain, or LangGraph
Preferred: familiarity with Datadog, Grafana, Conviva, and high-volume telemetry data
Preferred: experience with Databricks, Spark, or Snowflake

Benefits

Comp & perks

Bonus and/or long-term incentive units may be provided
Medical benefits
Financial benefits
Other benefits dependent on the level and position offered