Sr Machine Learning Engineer
Job Summary:
Technology is at the heart of Disney’s past, present, and future. Disney Entertainment and ESPN Product & Technology is a global organization of engineers, product developers, designers, technologists, data scientists, and more – all working to build and advance the technological backbone for Disney’s media business globally.
The team marries technology with creativity to build world-class products, enhance storytelling, and drive velocity, innovation, and scalability for our businesses. We are Storytellers and Innovators. Creators and Builders. Entertainers and Engineers. We work with every part of The Walt Disney Company’s media portfolio to advance the technological foundation and consumer media touch points serving millions of people around the world.
Here are a few reasons why we think you’d love working here:
- Building the future of Disney’s media: Our Technologists are designing and building the products and platforms that will power our media, advertising, and distribution businesses for years to come.
- Reach, Scale & Impact: More than ever, Disney’s technology and products serve as a signature doorway for fans' connections with the company’s brands and stories. Disney+. Hulu. ESPN. ABC. ABC News…and many more. These products and brands – and the unmatched stories, storytellers, and events they carry – matter to millions of people globally.
- Innovation: We develop and implement groundbreaking products and techniques that shape industry norms, and solve complex and distinctive technical problems.
Ad Platforms is responsible for Disney’s industry-leading ad technology and products – driving advertising performance, innovation, and value in Disney’s sports, news, and entertainment content, across all media platforms.
As part of the Decisioning Fleet, on the Selection squad you will help build services and models enabling efficient ad fills for ad breaks across Hulu, Disney+, ESPN, and others. You will directly contribute to optimizing ad selection to make sure viewers always see the right ad at the right time.
As a Senior Machine Learning Engineer of our team, you will apply your knowledge and skills to help us deliver scalable, efficient, maintainable, and testable software and apply ML solutions where needed.
Daily, you should bring:
- A desire to effectively communicate and collaborate across teams and systems.
- An understanding of the importance of project ownership.
- A passion for mentoring, learning, and adapting to a very dynamic environment.
- An understanding of micro-service encapsulation and loose coupling, and why they are important.
- An understanding of ML models and knowledge of how to leverage their use online and offline.
- An understanding of how to define technical and operational metrics to measure system health and manage risks.
- Kind fair and pragmatic approach.
- Designing, implementing, and testing logic to serve ads effectively adhering to various business requirements, using rule-based or ML-based solution in a high-throughput, low-friction environment.
- Enhancing system performance with proper monitoring and alerting.
- Interpreting product user stories and breaking them down into development tasks.
- Taking ownership of one or more of the team's domain areas.
- Using automated tools (AI) while following company policies.
- Being part of on-call rotations as per the team’s schedule.
Basic Qualifications:
- BS or MS in Computer Science / Engineering or relevant work experience.
- 5+ years of software engineering, specifically ML.
- Experience with Java
- Proficient in large-scale ML/DL platforms and tech stacks.
- Experience with machine learning tools like scikit-learn, Spark MLLib, PyTorch
- Experience with LLM-based applications using AWS Bedrock, Azure Cognitive Services, or Google's Vertex AI
- Experience with frameworks like LangGraph, Crew AI, and Strands SDK
- Experience with vector databases and retrieval-augmented generation
- Strong analytical and problem-solving skills and understanding of AI/ML.
- Good communication and collaboration across technical and business teams.
Preferred Qualifications:
- SpringBoot and related frameworks.
- Non-relational data stores like DynamoDB.
- Caching solutions such as Redis or Memcached.
- Data streaming like Apache Kafka or Kinesis.
- Cloud platforms such as AWS.
- DevOps tools like Terraform, Docker, and Kubernetes.
- Knowledge of the Ad Tech industry.