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
