Video Algorithms Intern, Video Coding (Gaussian Splatting), Fall 2026

Benefits

Parental leave

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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

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Learning budget

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Verification

Not verified checked Jun 13, 2026

Salary

$40-$110/hr From the posting source checked Jun 20, 2026

401(k) match

Reported from DOL Form 5500 industry filing (not employer-specific)

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

34% above the BLS role benchmark for software engineering aggregate.

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

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

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Entry From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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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

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Video Algorithms Intern, Video Coding (Gaussian Splatting), Fall 2026 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 Role Gaussian Splatting (GS) is a 3D/4D scene reconstruction technique that enables photorealistic novel-view synthesis with low rendering complexity, making it attractive for deployment on consumer devices such as TVs, streaming sticks, phones, and laptops. Realizing this vision requires addressing several open technical challenges, such as a significant reduction in model training/encoding time and more efficient compression. As part of the Video Algorithms team during this 24-week Fall internship, you will help us investigate the potential of GS as a future streaming format and explore possible improvements, with a focus on building towards a practical system. During the internship, you will: Explore GS model compression strategies using open datasets Contribute to early thinking on additional dataset needs for representative scenes. Characterize trade-offs among GS model size, training time, and rendered quality, and quantify the gap relative to streaming-rate targets Identify and experiment with strategies to reduce training/encoding time and/or to improve GS compression efficiency Design and implement a proof-of-concept (PoC) that showcases GS-based rendering on content of interest Who Are You? Currently pursuing a PhD in

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