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# Senior Research Scientist - Machine Learning System Expiring soon

- **Company:** BYTEDANCE INC.
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $218,400.0
- **Contract:** Permanent contract
- **Skills:** Systems Engineering, Artificial Neural Networks, C++ (Programming Language), Nvidia CUDA, Distributed Systems, Python (Programming Language), Machine Learning, Performance Tuning, Remote Direct Memory Access, Pytorch, Large Language Models, Deep Learning, Parallel Computation, TensorRT
- **Published:** September 1, 2026
- **Apply:** https://www.gamesjobsdirect.com/job/bytedance/senior-research-scientist-machine-learning-system/350469

## About the Role

Minimum Qualifications: - Bachelor's degree or above, major in computer/electronics/automation/software, etc. - Proficient in C/C++, proficient in algorithms and data structures, familiar with Python - Understand the basic principles of deep learning algorithms, be familiar with the basic architecture of neural networks and understand deep learning training frameworks such as Pytorch. Preferred Qualifications: - Proficient in GPU high-performance computing optimization technology on CUDA, in-depth understanding of computer architecture, familiar with parallel computing optimization, memory access optimization, low-bit computing, etc. - Familiar with TensorRT-LLM, ORCA, VLLM, etc. - Knowledge of LLM models, experience in accelerating LLM model optimization is preferred.

## Description

The Machine Learning (ML) System sub-team combines system engineering and the art of machine learning to develop and maintain massively distributed ML training and Inference system/services around the world, providing high-performance, highly reliable, scalable systems for LLM/AIGC/AGI In our team, you'll have the opportunity to build the large scale heterogeneous system integrating with GPU/NPU/RDMA/Storage and keep it running stably and reliably, enrich your expertise in coding, performance analysis and distributed system, and be involved in the decision-making process. You'll also be part of a global team with members from the United States, China and Singapore working collaboratively towards unified project direction. Responsibilities: - Responsible for developing and optimizing LLM inference framework. - Responsible for GPU and CUDA Performance optimization to create an industry-leading high-performance LLM inference engine.


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