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Research Engineer – AI Systems
Yotta LabsAI Systems Research Engineer at Yotta Labs focusing on optimizing AI systems and GPU architecture for multi-silicon computing. Join a visionary team rethinking AI infrastructure through innovation and collaboration.
Tech Stack
Tools & technologiesAWSPythonPyTorch
About the role
Key responsibilities & impact- 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.
Requirements
What you’ll need- 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
Benefits
Comp & perks- Competitive compensation with equity
- Flexible, remote work environment that values innovation and autonomy
ATS Keywords
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Hard Skills & Tools
High-Performance Kernel DesignAttention MechanismsMoE ImplementationGEMM OptimizationQuantization TechniquesCustom Operator DevelopmentGraph OptimizationDistributed Training SolutionsPerformance Profiling ToolsModel Architecture Understanding
Soft Skills
Problem-Solving SkillsCollaborative Work