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Research Engineer - AI Systems

Full-time

Yotta Labs

Role Description

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.

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.

Qualifications

  • 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.

Preferred Experience

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

Benefits

  • Be part of a visionary team aiming to redefine AI infrastructure and influence the future of multi-silicon AI computing.
  • Work on cutting-edge technologies that solve frontier AI infrastructure problems.
  • Collaborate with experts from leading institutions and tech companies.
  • Competitive compensation with equity.
  • Enjoy a flexible, remote work environment that values innovation and autonomy.

How to Apply

Interested candidates should apply directly or send their resume and a brief cover letter to View email address on us.fitly.work. Please include links to any relevant projects or contributions.

Vacancy posted a month ago
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