Machine Learning Scientist (L4/L5) - Multi-modal Algorithms for Games

Netflix

Remote

Quick summary

Work type
Remote
Location
Los Gatos, CALos Angeles, CA
Salary
$466,000–$750,000 / yr
Posted
36 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $206k
This role $608k
$88k most similar roles pay here $821k

This role pays more than 99% of similar roles. Most pay $175,740–$236,037 — the shaded band above. At the midpoint, this role pays about $608k versus about $206k 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 117 open roles on FindRole.

Listed pay typically runs $388,000–$619,000 across 113 roles with salary data.

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At a glance

TL;DR · Machine Learning Scientist (L4/L5) - Multi-modal Algorithms for Games

As a Machine Learning Scientist at the Studio Media Algorithms team, you will lead the research and development of Large Language Models (LLMs), Vision-Language Models (VLMs), and multi-modal foundations for games, focusing on inference efficiency. You will collaborate closely with the Games Studio R&D team to innovate algorithms that optimize models for cost, latency, and quality across various devices. Your daily tasks include fine-tuning LLMs and VLMs using PyTorch, optimizing model compression techniques like knowledge distillation and structural pruning, developing efficient Diffusion-based models for generative visuals, and integrating audio-visual models to enable low-latency interactions. You should have expertise in deep learning architectures such as Transformers and Diffusion, experience with algorithmic optimization, data-centric skills, and proficiency in Python and PyTorch. Additional knowledge in optimizing models for heterogeneous hardware and multimodal video generation is a plus.

What you'll do

  • Design and own the fine-tuning of LLMs and VLMs to enhance interactive game systems.
  • Lead model compression efforts using knowledge distillation and structural pruning for efficiency.
  • Develop and optimize Diffusion-based models for real-time image, video, and 3D generation in games.
  • Strategically integrate state-of-the-art open-source and commercial models with internal enhancements.
  • Optimize multi-modal interaction including audio, language, and vision models for low-latency performance.

What we're looking for

  • Deep expertise in Transformers and Diffusion architectures for LLMs and VLMs.
  • Proven track record in model optimization techniques like distillation and pruning.
  • Strong skills in data cleaning, curation, and synthetic data creation.
  • Experience evaluating and integrating SOTA open-source models with proprietary R&D.
  • Expert proficiency in Python and deep learning frameworks like PyTorch.
  • Ability to optimize models for various hardware including mobile and cloud GPUs.
  • Prior experience in audio-visual multimodal models and video generation.

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