Senior Machine Learning Engineer

The Walt Disney Company

Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$148,700–$199,400 / yr
Posted
6 days ago
Closes
Dec 31, 2026

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $219k
This role $174k
$135k most similar roles pay here $279k

This role pays less than 82% of similar roles. Most pay $187,252–$250,259 — the shaded band above. At the midpoint, this role pays about $174k versus about $219k for comparable roles.

Based on 240 similar postings.

Employer

About The Walt Disney Company

The Walt Disney Company is a diversified global entertainment and media enterprise operating in segments including Disney Parks, Experiences and Products; Entertainment (ABC, Hulu, Disney+); and ESPN. Industry: Entertainment & Media

The Walt Disney Company currently has 152 open roles on FindRole.

Listed pay typically runs $146,850–$190,300 across 148 roles with salary data.

Most-posted roles

View all roles at The Walt Disney Company

At a glance

TL;DR · Senior Machine Learning Engineer

As a Senior Machine Learning Engineer at Disney Entertainment & ESPN Technology, you will join a team dedicated to building and operating large-scale data infrastructure for real-time personalization and live sports experiences. Your day-to-day responsibilities include developing high-throughput streaming data pipelines, feature computation systems, and ML-adjacent services that ensure reliability and efficiency in production environments. You will work closely with senior engineers, data scientists, and platform teams to implement modern distributed data frameworks like Kafka, Kinesis, Spark, and Flink, ensuring low-latency data processing for real-time decision-making. The role requires proficiency in Python, Java, Scala, Go, or C++, as well as experience with cloud-native environments such as AWS, Kubernetes, and IaC tools. Ideal candidates have a background in building scalable ML systems and are familiar with feature stores, event-driven architectures, and operational best practices for production data infrastructure.

What you'll do

  • Build and maintain high-throughput batch and streaming data pipelines for ML use cases.
  • Develop real-time feature computation systems to support online ML services.
  • Contribute to scalable service patterns including autoscaling and resiliency mechanisms.
  • Instrument data infrastructure with metrics, logging, and alerting for production operations.
  • Identify and remediate operational risks in data pipeline failures and performance regressions.

What we're looking for

  • 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 data technologies (e.g., Kafka, Kinesis, Spark).
  • Proficiency in Python and working knowledge of Java, Scala, Go, or C++.
  • Experience operating cloud-native environments (AWS, containers, Kubernetes).
  • Familiarity with observability and operational best practices for production systems.
  • Bachelor’s or Master’s degree in Computer Science, Data Engineering, Machine Learning.

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