Research Engineer - AI Systems

Yotta Labs

4d•Remote

About The Position

We are seeking a highly motivated AI Systems Research Engineer specializing in Trainium, GPU kernels, and LLM systems optimization. You will work at the intersection of AI Systems, Compiler and Runtime Optimization, Distributed Training & Inference, GPU/Accelerator Kernel Development, and Large Language Model Infrastructure. Your work will directly impact the scalability and performance of AI applications deployed on our platform.

Requirements

Proficiency in AI programming languages such as Python and C++.
Deep understanding of GPU architecture and performance optimization.
Experience with CUDA, Triton, ROCm/HIP, or AWS Neuron.
Strong understanding of AI frameworks (e.g., PyTorch, Dynamo, LMCache), model architectures and profiling tools (e.g. Nsight, ROCm Profiler, or Neuron Profiler).
Strong problem-solving skills and the ability to work in a collaborative, remote environment.
A background in computer science, engineering, or a related field is preferred.

Nice To Haves

Contributions to open-source AI infra projects like vLLM, SGLang, PyTorch, or Triton.
Experience with with FlashAttention, PagedAttention, MoE, RLHF, or distributed AI systems.
Publications in top-tier conferences like MLSys, OSDI, SOSP, NSDI, SC, HPCA, or ISCA

Responsibilities

Design and implement high-performance kernels for Attention, MoE, GEMM, collective communication, and quantization.
Optimize kernels for NVIDIA, AMD, and AWS Trainium.
Develop custom operators and graph optimizations using Neuron SDK, PyTorch/XLA, Torch Dynamo, and Neuron Compiler.
Improve performance of vLLM, SGLang, TensorRT-LLM, and custom inference runtimes.
Design scalable distributed training and inference solutions across thousands of accelerators.
Contribute to open-source projects, publish technical findings and engage with the developer community.