Senior Machine Learning Engineer

Senior Machine Learning Engineer

Be part of the story

BUILD SOMETHING BIGGER THAN YOURSELF 

The Walt Disney Company, together with its subsidiaries and affiliates, is a leading diversified international family entertainment and media enterprise with the following business segments: Disney Entertainment, ESPN, Disney Parks, and Experiences and Products. From humble beginnings as a cartoon studio in the 1920s to its preeminent name in the entertainment industry today, Disney proudly continues its legacy of creating world-class stories and experiences for every member of the family. Disney’s stories, characters and experiences reach consumers and guests from every corner of the globe. With operations in more than 40 countries, our employees and cast members work together to create entertainment experiences that are both universally and locally cherished.

How will you contribute to our magical experience?  

Media Engineering powers the core technology behind Disney+, Hulu, ESPN, and future streaming innovations. The Content Library team sits at the heart of this ecosystem, owning the systems responsible for title metadata and content descriptors that shape user experiences across our platforms.

We are seeking a Senior Machine Learning Engineer specializing in deployment and ML platform development to help evolve the intelligence behind our metadata systems. You’ll focus on developing machine learning models to improve entity resolution, duplicate detection, and metadata quality at scale — foundational problems with deep technical and business impact.

 This is a deployment-focused MLE role centered on building the infrastructure and services that bring ML models to production. You’ll own data pipelines, feature engineering, and model deployment, while also contributing to model development and evaluation where production constraints, data quality, or real-world performance inform modeling decisions.

The Senior Machine Learning Software Engineer will be responsible for: 

• Build and maintain robust data pipelines and services to support model deployment at scale
• Own the ML deployment lifecycle: from feature engineering and inference pipelines to monitoring and model rollout
• Collaborate with ML engineers and data scientists to productionize models with reliability and performance in mind
• Develop and deploy backend services using Java or Python, integrating with AWS infrastructure (e.g., S3, SageMaker, Lambda, SQS)
• Automate workflows and implement tooling for continuous delivery, testing, and validation of ML models
• Ensure service availability and performance through observability, alerting, and operational excellence
• Champion best practices in MLOps, infrastructure design, and scalable system architecture

What we need from you to be part of this story:

• 5+ years of backend engineering experience, with strong proficiency in Python and/or Java
• Advanced level of English.
• Proven track record deploying ML models into production systems
• Deep familiarity with AWS services like SageMaker, Lambda, S3, SQS, and Glue
• Experience building scalable data pipelines and feature engineering workflows
• Solid understanding of ML lifecycle, including inference, monitoring, and versioning
• Proficiency in working with both relational (PostgreSQL, MySQL) and NoSQL (DynamoDB, ElastiCache) databases
• Strong CS fundamentals: data structures, algorithms, and software design
• Working knowledge of machine learning modeling concepts, including embeddings, similarity metrics, and supervised classification
• Comfort collaborating on model design discussions, even when not acting as the primary model owner.
• Familiarity with Kafka, Kinesis, or other messaging/streaming platforms
• Ability to work autonomously in agile, cross-functional teams
• Experience with natural language processing (NLP) or metadata classification. (Nice to have)
• Familiarity with Elasticsearch or other search/indexing platforms. (Nice to have)
• Experience optimizing feature stores or building pipelines for large-scale ML systems. (Nice to have)
• Exposure to front-end development (ReactJS) to support full-stack integration of ML services. (Nice to have)
• Experience training or fine-tuning ML models using frameworks such as PyTorch, TensorFlow, or scikit-learn (Nice to have)
• Prior exposure to model evaluation techniques, offline metrics, and experimentation workflows (Nice to have)

​Additional Information: 

At Disney, we believe it takes great people to create memorable experiences, products and services our consumers know and love. We are a team of storytellers and hire under equal opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, disability and gender identity. We foster a corporate culture of belonging and inclusiveness, which empowers our staff and company to thrive. At Disney, everyone has the opportunity to speak up and participate, grow and share ideas.

“You can design and create and build the most wonderful place in the world. But it takes people to make the dream a reality.” Walt Disney