Staff Software Engineer (L6), Developer Productivity - Platform Systems

Netflix

Confirmed live today High trust
Remote

Quick summary

Work type
Remote
Location
Remote
Salary
$600,000–$1,066,000 / yr
Employment
Full-time
Posted
69 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $200k
This role $833k
$33k most similar roles pay here $1177k

This role pays more than 99% of similar roles. Most pay $169,550–$230,662 — the shaded band above. At the midpoint, this role pays about $833k versus about $200k for comparable roles.

Based on 240 similar postings.

Employer

About Netflix

Netflix is the world''s leading streaming entertainment service, offering a vast library of TV series, films, documentaries, and original content to subscribers in over 190 countries. Industry: Streaming Entertainment & Media

Netflix currently has 71 open roles on FindRole.

Listed pay typically runs $440,000–$725,000 across 59 roles with salary data.

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View all roles at Netflix

At a glance

TL;DR · Staff Software Engineer (L6), Developer Productivity - Platform Systems

The Staff Software Engineer (L6) - Developer Productivity joins the Platform Systems team within AIMS Engineering to own the developer experience for ML practitioners. This role focuses on the build, test, and iteration loop, ensuring that researchers can move ideas from notebooks to production experiments efficiently. You will design, build, and operate large-scale build and CI/CD systems, manage local and remote development environments, and develop self-service internal platforms. Key responsibilities include identifying engineering friction, instrumenting workflows to measure productivity, and productionizing GenAI-powered developer tooling like automated code reviews. Required skills include deep proficiency in Python, working knowledge of JVM languages like Scala or Java, and experience with distributed build systems such as Bazel, Buck, or Pants, alongside large-scale data frameworks like Spark or Beam.

What does a Software Engineer earn in Remote?

Median $206500 from 303 postings across 46 companies.

See salary data

What you'll do

  • Own the end-to-end developer experience for ML practitioners, including local/remote environments and CI/CD pipelines.
  • Design and operate large-scale build systems to maintain fast iteration times as the codebase grows.
  • Identify and remove friction in engineering workflows by designing tooling and abstractions at the root.
  • Build and maintain internal developer platforms and self-service tools to reduce operational burdens on ML teams.
  • Instrument and measure developer productivity metrics like build times and iteration speed to prioritize investments.
  • Drive adoption of new tooling through documentation, migration support, and hands-on partnership with research teams.
  • Set technical standards for developer tooling and provide architectural guidance through design reviews.
  • Evaluate, integrate, and productionize GenAI-powered developer tooling to improve engineering velocity.

What we're looking for

  • Significant experience building and operating developer productivity infrastructure like build systems, CI/CD, or internal platforms at scale.
  • Strong software engineering fundamentals with deep proficiency in Python and working proficiency in at least one JVM language like Scala or Java.
  • Hands-on experience with distributed build systems such as Bazel, Buck, or Pants.
  • Hands-on experience with large-scale distributed data or compute frameworks such as Spark or Beam.
  • Working understanding of GenAI-powered developer tooling and experience using these tools effectively in an engineering practice.
  • Comfort with parallel and distributed computing and experience operating systems at a scale where naive approaches fail.
  • Ability to drive cross-team technical programs and earn adoption without formal authority.
  • Experience with ML-specific developer tooling, open-source contributions, or high-performance computing environments (preferred).

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