Yotta Labs

Systems Engineer

• Implement and optimize compute kernels for Attention, GEMM, MoE, and quantization on NVIDIA, AMD, or AWS Trainium.
• Build custom operators using CUDA, Triton, ROCm/HIP, or the Neuron SDK with PyTorch/XLA.
• Profile and improve inference performance in vLLM, SGLang, and our custom runtimes — kernel fusion, scheduling, KV-cache and memory optimizations.
• Build benchmarks, chase down performance regressions, and turn profiler traces into concrete speedups.
• Ship code upstream to open-source AI infrastructure projects, with tests and documentation.

Research Engineer Intern – AI Systems

• 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.

Research Engineer Intern – AI Systems

Research Engineer – AI Systems