Creative Tech Researcher 5

Workman Labs; Los Angeles, Northern (CA, KY); Hybrid; USD 466,000 - 750,000; Full time

Job summary

Netflix's Creative Technology Research team in Los Angeles seeks a senior machine learning researcher to build foundational image and video generation models for filmmaking. You will own model architecture, train on large distributed systems, and shape data strategies for scalable experimentation.

The role emphasizes data-centric preparation, cross-team evaluations, and potential contributions to open-source projects, with a focus on rapid innovation and impact.

Qualifications

• Deep understanding of deep learning fundamentals (Transformers, Diffusion models).
• Data-centric approach to preparation and curation.
• Proven experience training/inferring large-scale models on distributed clusters.
• Bonus: experience delivering high-impact products or open-source projects.

Responsibilities

• Foundational modeling: develop and optimize model architectures for image and video generation and editing.
• Data strategy: prepare and organize data for training large-scale image and video generation models.
• Large-scale training: implement efficient distributed training and data-loading infrastructure for large clusters.
• Evaluation frameworks: conduct cross-team evaluations to gather feedback and build representative benchmarks.

Skills

Transformers

Diffusion models

Distributed training

Impact mindset

Data-centric data preparation

Job description

Netflix's Creative Technology Research team (formed through the Interpositive acquisition and operating as a startup backed by Netflix's resources) is hiring a senior machine learning researcher to develop foundational image and video generation models for filmmaking — owning model architecture, large-scale distributed training, data strategy, and evaluation.

$466,000 – $750,000 / yr

Location

—

Seniority

Compared with 9 other Research roles: Common across similar roles Unique to this role

What you’ll do

Responsibilities

• Foundational modeling: develop and optimize model architectures for image and video generation and editing Common
• Data strategy: prepare and organize data for training large-scale image and video generation models Common
• Large-scale training: implement efficient distributed training and data-loading infrastructure for large clusters
• Evaluation frameworks: conduct cross-team evaluations to gather feedback and build representative benchmarks

What you’ll need

Experience

• Deep understanding of deep learning fundamentals (Transformers, Diffusion models) Common
• Data-centric approach to preparation and curation Unique
• Proven experience training/inferring large-scale models on distributed clusters Common
• Impact-oriented mindset for fast-paced innovation
• Bonus: experience delivering high-impact products or open-source projects