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The Walt Disney Company is a global entertainment business built around storytelling, characters, and guest experiences. Its operations span theme parks and resorts, media networks, film studios, and interactive media, with products and experiences reaching audiences across platforms and devices worldwide. Founded in 1923, Disney brings together a large international workforce across entertainment, hospitality, travel, and food and beverage, while maintaining a focus on privacy, transparency, and compliance in its handling of consumer data.
Senior Machine Learning Engineer
Build and deploy scalable machine learning models, pipelines, and production systems for Disney’s Commerce technology business. Guide ML architecture, MLOps practices, and technical work across engineering initiatives.
United States
California
Florida
Washington$137,200 – $202,400 / year
HybridFull-timeSeniorEnglish RequiredMachine Learning EngineerDescription
- Design and develop machine learning models, pipelines, and production systems.
- Advance ML components through your work and collaboration with other engineers.
- Create technical solutions that meet specifications and shape future ML initiatives.
- Deliver ML projects and major model improvements using new or existing technologies.
- Define specifications for assigned ML components, projects, and model enhancements.
- Review and write code for model training, evaluation, and inference pipelines.
- Help set the architectural direction for ML platforms and data infrastructure.
- Design ML components for projects and document their specifications.
- Build and lead workflows spanning data ingestion through model serving.
- Coordinate deliverables with data science, data engineering, and product teams across the organization.
- Develop system specifications for assigned ML projects.
- Provide senior technical guidance to less experienced ML engineers and data scientists.
- Lead teams in problem analysis, model debugging, and issue resolution.
Requirements
- At least five years of relevant experience designing, training, and deploying machine learning models at scale in production.
- Experience with Python and ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
- Strong grasp of supervised and unsupervised learning, model evaluation, and feature engineering.
- Expertise in MLOps practices, including model versioning, experiment tracking, CI/CD for ML, and model monitoring.
- Experience with cloud ML services and infrastructure such as AWS SageMaker, EC2, and S3.
- Experience with data pipeline and orchestration tools such as Airflow, Spark, and Kafka.
- Familiarity with databases and storage technologies such as DynamoDB, Redshift, and NoSQL.
- Familiarity with Docker, Kubernetes, and containerization.
- Familiarity with data manipulation tools.
- Experience with Snowflake is required.
- Experience with large-scale recommendation systems, personalization, NLP, or computer vision.
- Experience with real-time ML inference and low-latency serving architectures.
- Familiarity with LLMs and integrating generative AI into production systems.
- Java experience, including Spring Boot, is a plus.
- Bachelor’s degree in Computer Science, Statistics, Mathematics, or a similar field, or related work experience.
Benefits
- A bonus and/or long-term incentive units may be included in the compensation package.
- Medical benefits.
- Financial benefits.
- Other benefits.
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