Senior Machine Learning Engineer
disney entertainment sportsGlendale, CA
$144,100 - $193,200 per year
APPLY (opens in a new tab)Senior Machine Learning Engineer
disney entertainment sportsGlendale, CASenior L5
$144,100 - $193,200 per year
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related ServicesSoftware PublishersCustom Computer Programming Services
APPLY NOW (opens in a new tab)Join ESPN to build and run the distributed data and machine learning infrastructure behind real-time sports personalization and live experiences.
Responsibilities:
- Build and maintain high-throughputbatch and streaming data pipelinesfor ML, analytics, and real-time decisioning
- Implementdata ingestion, enrichment, aggregation, and transformationusing modern distributed data frameworks
- Deliver pipelines that meetlatency, reliability, and data qualityneeds for downstream ML and product teams
- Develop and operate systems forreal-time feature computation and deliveryused by online ML services
- Partner with applied ML and data science teams to enable production ML workflows through reliable data systems
- Work withfeature storesandevent-driven architecturesto keep offline and online data consistent
- Improvedata freshness , schema evolution, andbackward compatibilityfor streaming environments
- Build and operate ML-adjacent services such asinference inputs, feature APIs, and data access layers
- Contribute to scalable service patterns includingautoscaling, rollout strategies, and resiliency mechanisms
- Collaborate with platform and SRE teams to improveavailability, performance, and cost efficiency
- Instrument data and ML infrastructure withmetrics, logging, and alertingfor production operations
- Participate inon-call rotationsandincident responsefor data and ML platforms
- Diagnose and remediatedata pipeline failures, performance regressions, and operational risks
- Participate indesign reviews, code reviews, and technical discussions
- Follow established platform standards and contributeincremental improvementsover time
- Requirements5+ yearsof industry experience building data-intensive or ML-adjacent systems in production
- Experience building and operatinglarge-scale data or ML systemsin production.
- Strong fundamentals indistributed systemsanddata processing architectures
- Hands-on experience with streaming and batch technologies such asKafka, Kinesis, Spark, Flink, or equivalent
- Proficiency inPythonand working knowledge ofJava, Scala, Go, or C++Experience operating incloud-native environmentsincludingAWS, containers, Kubernetes, and
- IaC tools
- Familiarity withobservabilityand operational best practices for production systems
- Strong collaboration skills across engineering and data teams
- Experience supportingreal-time personalization, recommendation, or analyticssystems
- Familiarity withfeature stores , event-driven architectures, andreal-time ML pipelines
- Exposure to ML infrastructure concepts includinginference pipelines, data validation, and model lifecycle tooling
- Experience optimizing data systems forlatency, throughput, and cost efficiency
- Understanding ofexperimentation platformsand data instrumentation for online systems
- TechnologiesKafka, Kinesis
- Spark, FlinkPythonJava, Scala, Go, C++AWSContainers, Kubernetes, IaC tools
- Feature stores
- EducationBachelor’s or Master’s degree inComputer Science, Data Engineering, Machine Learning, or a related field
- Location and Salary
Location: Glendale, CA (onsite)
Compensation: USD 144,100 - 193,200 per year
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Level
Senior L5
Salary
$144,100 - $193,200 per year
Location
Glendale, CA
Occupation
Data Scientists
Industry
Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services
Posted
today