Sr Machine Learning Engineer

The Senior Machine Learning Engineer role supports Disney Entertainment and ESPN Product & Technology, within the Ad Platforms Decisioning Fleet/Selection squad. The position focuses on building services and machine learning models that improve ad fill efficiency across Hulu, Disney+, ESPN, and other properties, with emphasis on scalable, performant, and testable software in a microservices environment.

Key Responsibilities

• Design, implement, and test ad-serving logic that satisfies business criteria using rule-based or ML-based approaches for a high-throughput, low-latency microservices environment.
• Improve system observability by implementing appropriate metrics, monitors, and alerting.
• Review product user stories and translate them into actionable tasks across both frontend and backend components.
• Own one or more domain areas within the team.
• Use automated tools (AI) in alignment with company policy.
• Participate in on-call rotations according to the team’s escalation policy and support schedule.

Required Qualifications

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

Technologies

Java, scikit-learn, Spark MLLib, pytorch, AWS Bedrock, Azure Cognitive Services, Google's Vertex AI, LangGraph, Crew AI, strands sdk, vector databases, retrieval-augmented generation, SpringBoot, Spring, DynamoDB, Redis, ValKey, MemCache, Apache Kafka, Kinesis, AWS, Terraform, Docker, Kubernetes

What You Will Do Daily

• Communicate and collaborate across teams and systems to support delivery.
• Apply an understanding of project ownership.
• Demonstrate interest in mentoring, learning, and adapting in a dynamic, fast-paced environment.
• Work with micro-service encapsulation and loose coupling principles.
• Understand ML models and how to leverage them in both online and offline settings.
• Define technical and operational metrics to measure system health and manage risk.
• Practice kindness and pragmatic optimism.

Preferred Qualifications

• Experience with SpringBoot and related Spring projects.
• Experience with non-relational database technologies such as DynamoDB.
• Experience with caching datastores including Redis, ValKey, or MemCache.
• Experience with data streaming mechanisms such as Apache Kafka and/or Kinesis.
• Experience with AWS.
• Experience with modern DevOps tools such as Terraform, Docker, and Kubernetes.
• Domain knowledge in the Ad Tech industry.

Location and Compensation

• Location: Seattle, WA (onsite)
• Salary: USD 141,900 - 199,400 per year
• Office requirement: Engineers are expected to be in the office four days a week.
• Hiring locations: Glendale, Seattle, San Francisco, or Santa Monica