Research Engineer Intern - AI Systems

Yotta Labs is building the next generation multi-silicon AI cloud and runtime platform to power the world’s most demanding AI workloads. They are seeking a highly motivated Research Engineer Intern to work on Trainium, GPU kernels, and LLM systems optimization, owning a well-scoped project that impacts AI applications deployed on their platform.

What you'll do:

• 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

What they're looking for:

• Currently pursuing a BS, MS, or PhD in Computer Science, Computer Engineering, or a related field
• Solid programming skills in Python and familiarity with C++
• Understanding of GPU/accelerator architecture fundamentals (memory hierarchy, parallelism, occupancy) from coursework, research, or projects
• Experience writing CUDA, Triton, ROCm/HIP, or Neuron kernels — class projects and personal projects count
• 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 independently in a collaborative, remote environment
• Contributions to open-source AI infra projects like vLLM, SGLang, PyTorch, or Triton
• Familiarity with LLM inference internals — FlashAttention, PagedAttention, continuous batching, speculative decoding, MoE, or quantization
• Experience with profiling tools (e.g. Nsight, ROCm Profiler, Neuron Profiler, or PyTorch Profiler) and performance debugging on real workloads
• Publications in top-tier conferences like MLSys, OSDI, SOSP, NSDI, SC, HPCA, or ISCA

Benefits:

• Flexible remote work environment
• Direct mentorship from engineers from leading institutions and tech companies
• Access to serious hardware — latest-generation NVIDIA GPUs, AMD accelerators, and AWS Trainium at scale
• A fast path to a full-time return offer for top performers