FewerJobs.
All jobs

Machine Learning Manager - Localization Algorithms

Netflix - USA - Remote | Los Angeles,California,United States of America | Los Gatos,California,United States of America

Posted Feb 3, 2026

Benefits

Parental leave
Not verified
Non-birth-parent leave
Not verified not verified - source URL not recorded
Family-building benefits
  • Fertility benefits: Not verified
  • Adoption assistance: Not verified
  • Surrogacy assistance: Not verified
Mental health support
Offered From the posting source checked Jun 20, 2026
Relocation assistance
Not verified
Childcare support
Not verified
Learning budget
Not verified
Verification
Not verified checked Jun 13, 2026
Salary
$523K-$920K From the posting source checked Jun 20, 2026
401(k) match
Reported from DOL Form 5500 industry filing (not employer-specific)

Was this benefit information wrong? Tell us.

Market context

U.S. role benchmark (BLS OEWS)
$81,444 U.S. median for this role
Projected growth (BLS Employment Projections)
+6.9% - Faster than average

786% above the BLS role benchmark for healthcare aggregate.

Posted salary is far from this role benchmark; treat it as low confidence.

Matched to SOC 29-1141 - Healthcare aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function
Healthcare From the posting source checked Jun 20, 2026
Seniority
Mid From the posting source checked Jun 20, 2026
Work mode
Remote From the posting source checked Jun 20, 2026
In-office days
0 days From the posting source checked Jun 20, 2026

Schedule

Shift type
Not verified
Weekend work
Not verified

Company

Company stage
Public-company From the posting source checked Jun 20, 2026
Equity
Offered Verified - SEC 10-K source checked Jun 20, 2026

Application

Cover letter
Not verified
Assessment
Not verified
Deadline
Not stated

Where they hire

State eligibility is not yet verified.

About this role

Machine Learning Manager - Localization Algorithms USA - Remote | Los Angeles,California,United States of America | Los Gatos,California,United States of America At Netflix, our mission is to entertain the world. Together, we are writing the next episode - pushing the boundaries of storytelling, global fandom and making the unimaginable a reality. We are a dream team obsessed with the uncomfortable excitement of discovering what happens when you merge creativity, intuition and cutting-edge technology. Come be a part of what's next. The Localization Data Science and Engineering team is at the forefront of removing language barriers and providing a stellar member experience to all our members regardless of their language preferences. We are responsible for the translation and cultural adaptation of all aspects of member interaction, including beautiful localized user interfaces, subtitles, and dubbing of award-winning Netflix originals. We are seeking an experienced Machine Learning leader to lead a team of Research Scientists and Machine Learning Engineers working on multimodal LLM and audio algorithms . You will support a highly talented team in developing cutting‑edge algorithms and systems, and collaborate closely with cross‑functional partners to enhance localization experiences for Netflix members around the world. Responsibilities Lead a broad portfolio of end-to-end initiatives in multimodal LLM and audio algorithms to achieve Netflix's ambitious localization goals. Mentor, support, and inspire a team of Research Scientists and Machine Learning Engineers, amplifying their impact and fostering their career growth. Partner with technical leads on defining area strategy, planning and executing projects, and developing talent. Set

Read the full description at explore.jobs.netflix.net. FewerJobs shows a preview and links to the original posting.

Apply at explore.jobs.netflix.net

Apply link not verified; last-live date unavailable.

What verified means

Verified means a displayed claim has field-level provenance to a source FewerJobs pulled: a government or employer source, or the original job posting. Posting-sourced facts are employer-stated and are labeled separately from government records.

Related jobs