LLM Training & Inference Scientist (GPU-Optimized)

ByteDance; San Jose (CA); On-site; USD 212,800 - 450,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) savings plan with company match

Paid parental leave

Paid holidays and sick days

Paid Personal Time

Wellbeing benefits

Job summary

ByteDance is seeking talented PhD candidates to develop and optimize machine learning training frameworks in San Jose, California. As part of AML-MLsys, you'll work on cutting-edge AI projects involving large language models (LLMs).

The role requires proficiency in algorithms, data structures, and deep learning principles, alongside knowledge of Python and CUDA. Employees will enjoy comprehensive benefits including medical, dental, and vision insurance from day one.

Qualifications

• Currently pursuing a PhD in computer science, automation, electronics engineering or a related technical discipline.
• Proficient in algorithms and data structures, familiar with Python.
• Understand the basic principles of deep learning algorithms and training frameworks.

Responsibilities

• Develop and optimize LLM training & inference & Reinforcement Learning framework.
• Work closely with model researchers to scale LLM training & Reinforcement Learning.
• Optimize GPU and CUDA performance for high-performance LLM training.

Skills

Algorithms and data structures

Python

Deep learning principles

Education

Currently pursuing a PhD in computer science or related field

Tools

Pytorch

CUDA

Job description

ByteDance is seeking talented PhD candidates to develop and optimize machine learning training frameworks in San Jose, California. As part of AML-MLsys, you'll work on cutting-edge AI projects involving large language models (LLMs).

The role requires proficiency in algorithms, data structures, and deep learning principles, alongside knowledge of Python and CUDA. Employees will enjoy comprehensive benefits including medical, dental, and vision insurance from day one.