Senior Machine Learning Engineer, Ad Platforms

The Walt Disney Company•Glendale, CA

22d•Onsite

About The Position

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 MLE of our team, you will apply your knowledge and skills to help us deliver scalable, performant, maintainable, and testable software and apply ML solutions where needed. Daily, you should bring: A willingness and 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 and fast-paced 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 to manage risk. Kindness and pragmatic optimism.

Requirements

BS or MS in Computer Science / Engineering or relevant work experience.
5+ years of software engineering experience.
Proficiency with Java
Proficient in large scale ML/DL platforms and processing tech stack.
Experience in large scale machine learning using tools such as scikit-learn, Spark MLLib, pytorch
Experience with LLM-based application development, using LLM-as-a-service providers such as AWS Bedrock, Azure Cognitive Services, or Google's Vertex AI
Experience using frameworks such as LangGraph, Crew AI, and strands sdk for developing agents
Experience with vector databases and retrieval-augmented generation
Demonstrable analytical / problem-solving skills.
Strong knowledge of and experience implementing AI/ML technologies and applying mathematical and statistical concepts.
Great communication, collaboration skills, and a strong teamwork ethic with both technical and non-technical audiences.

Nice To Haves

Experience with: SpringBoot and related Spring projects.
Non-relational database technologies like DynamoDB.
Caching datastores such as Redis, ValKey or MemCache.
Data Streaming Mechanisms such as Apache Kafka and/or Kinesis.
Cloud platforms such as AWS.
Modern DevOps tools such as Terraform, Docker, and Kubernetes.
Domain knowledge in the Ad Tech industry.

Responsibilities

Designing, implementing, and testing logic to serve ads effectively adhering to various business criteria either with rule based or ML based solutions in a high-throughput, low-latency microservices environment.
Enhancing systems’ observability with proper metrics, monitors, and alerts.
Reading and understanding product user stories, and then translating them into actionable tasks for both frontend and backend components.
Taking ownership of one or more of the team's domain areas.
Understanding and using automated tools (AI) while adhering to company policy.
Available for On-Call rotations based on the team’s escalation policy and support schedule.

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