Research Engineer - AI Systems

Yotta Labs · Remote · United States · Hong Kong · Canada · Singapore ·
Fully remoteFull-timeMiddle3–5 years
COMPENSATION
€•• – ••k
0 applicants so far

Listed on the employer's job board (Ashby)

  • Fully remote (Global)
  • AI Systems Research
  • C++ and Python
  • GPU & Trainium
  • Full-time position

Join Yotta Labs to build a multi-silicon AI cloud platform that powers demanding workloads. You will optimize performance and economics for training and inference across heterogeneous hardware, including GPUs and AWS Trainium.

As an AI Systems Research Engineer, you will work on kernel development, runtime optimization, and distributed systems. Your contributions will directly enhance the scalability of AI applications deployed on the company's infrastructure.

What you'll do

  • Design high-performance kernels for Attention, MoE, GEMM, and quantization
  • Optimize kernels for NVIDIA, AMD, and AWS Trainium accelerators
  • Develop custom operators using Neuron SDK, PyTorch/XLA, and Torch Dynamo
  • Improve performance of vLLM, SGLang, TensorRT-LLM, and custom runtimes
  • Design scalable distributed training and inference solutions
  • Contribute to open-source projects and publish technical findings

What you'll need

  • Proficiency in Python and C++ for AI programming
  • Deep understanding of GPU architecture and performance optimization
  • Experience with CUDA, Triton, ROCm/HIP, or AWS Neuron
  • Knowledge of AI frameworks like PyTorch, Dynamo, and LMCache
  • Familiarity with profiling tools such as Nsight or ROCm Profiler
  • Strong problem-solving skills for collaborative remote work
  • Background in computer science, engineering, or related field

Nice to have

  • Contributions to open-source AI infra projects like vLLM or PyTorch
  • Experience with FlashAttention, PagedAttention, MoE, or RLHF
  • Publications in top-tier conferences like MLSys, OSDI, or SC

Stack

  • Python
  • C++
  • CUDA
  • Triton
  • ROCm
  • AWS Neuron
  • PyTorch
  • Torch Dynamo
  • vLLM
  • SGLang
  • TensorRT-LLM

How you'll work

  • Fully remote position available globally
  • Flexible work environment valuing autonomy

What you get

  • Competitive compensation package
  • Equity ownership opportunities
  • Collaboration with experts from leading institutions