Real Time Features Developer Jobs

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Today

Senior Machine Learning Engineer

Disney Entertainment & Sports LLC Glendale, CA

Glendale, CA

Today

$144k - $193k/yr Full time Artificial Intelligence Automation AWS

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Job Description

ESPN is expanding large-scale data infrastructure and real-time processing platforms to support next-generation personalization and live sports experiences. As a Senior Machine Learning Engineer at Disney Entertainment & Sports LLC, you will build and operate distributed data and ML infrastructure designed for high-throughput, low-latency processing and production ML use cases.

What you’ll do

Build and maintain high-throughput batch and streaming data pipelines for ML, analytics, and real-time decisioning.
Implement ingestion, enrichment, aggregation, and transformation workflows using modern distributed data frameworks.
Deliver pipelines that meet latency, reliability, and data quality expectations for downstream ML and product teams.
Develop and operate systems for real-time feature computation and feature delivery to online ML services.
Use feature stores and event-driven architectures to keep offline and online data consistent.
Improve data freshness, schema evolution, and backward compatibility in streaming environments.
Build and operate ML-adjacent services such as inference inputs, feature APIs, and data access layers.
Support scalable service patterns including autoscaling, rollout strategies, and resiliency mechanisms.
Partner with platform/SRE teams to improve availability, performance, and cost efficiency.
Instrument production systems with metrics, logging, and alerting to enable reliable operations.
Participate in on-call rotations and incident response for data and ML platforms.
Investigate and remediate pipeline failures, performance regressions, and operational risks.
Collaborate with applied ML and data science teams to enable production ML workflows through dependable data systems.
Contribute to design reviews, code reviews, and technical discussions while following platform standards.

What you bring

5+ years of industry experience building data-intensive or ML-adjacent systems in production.
Proven experience building and operating large-scale data or ML systems in production.
Strong fundamentals in distributed systems and data processing architectures.
Hands-on experience with streaming and batch technologies such as Kafka, Kinesis, Spark, Flink, or equivalents.
Proficiency in Python and working knowledge of Java, Scala, Go, or C++.
Experience operating in cloud-native environments using AWS, containers, Kubernetes, and IaC tools.
Familiarity with observability and operational best practices for production systems.
Experience supporting real-time personalization, recommendation, or analytics systems.
Familiarity with feature stores, event-driven architectures, and real-time ML pipelines.
Exposure to ML infrastructure concepts such as inference pipelines, data validation, and model lifecycle tooling.
Experience optimizing data systems for latency, throughput, and cost efficiency.
Understanding of experimentation platforms and data instrumentation for online systems.
Strong collaboration skills across engineering and data teams.

Tools and technologies

Kafka, Kinesis, Spark, Flink
Python, Java, Scala, Go, C++
AWS, containers, Kubernetes, IaC tools
Feature stores

Location and compensation

Glendale, CA (onsite). Salary range: USD 144,100 - 193,200 per year.

Education

Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning, or a related field.

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