Creative Tech Researcher 4

Workman Labs; Los Angeles (CA); Hybrid; USD 300,000 - 537,000; Full time

Job summary

Netflix's Creative Technology Research team is hiring a senior machine learning researcher to develop next-generation image and video generation models, owning model architecture, large-scale distributed training, data strategy, and evaluation. The role emphasizes hands-on leadership in scalable systems and bridging innovation with deployment in a fast-paced environment.

The position seeks a researcher who can drive end-to-end ML experimentation, collaborate across teams, and contribute to

Qualifications

• Experience in data preparation and curation for ML workflows.
• Proven track record training and inferring large-scale models distributively on large clusters.
• Ability to operate in fast-paced, innovative environments on high-visibility problems.
• 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: build benchmarks and run evaluations to ensure quality across model outputs.

Skills

Data preparation

Distributed training

Fast-paced environment

Open-source experience

Job description

Netflix's Creative Technology Research team (recently acquired from Interpositive and operating as a startup backed by Netflix's global resources) is hiring a machine learning researcher to develop next-generation image and video generation models — owning model architecture, large-scale distributed training, data strategy, and evaluation.

$300,000 – $537,000 / yr

Location

—

Seniority

Senior

Compared with 15 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 Common
• Evaluation frameworks: build benchmarks and run evaluations to ensure quality across model outputs

What you'll need

Experience

• Data-centric skills in data preparation and curation
• Proven experience training and inferring large-scale models distributively on large clusters Common
• Ability to operate in fast-paced, innovative environments on high-visibility problems
• Bonus: experience delivering high-impact products or open-source projects