Inception
Member of Technical Staff, Kernels
San Mateo, USA · Staff+
Sponsorship not specifiedDetected 134 days ago
PythonGoRustC++Distributed SystemsAWSGCPAzureDockerKubernetesCI/CDMachine LearningDeep LearningTensorFlowPyTorchNLP
About the role
- We're looking for engineers and scientists to design, optimize, and maintain the compute foundations that power large-scale language model training and inference.
- You will develop high-performance ML kernels, enable efficient low-precision arithmetic, and improve the distributed compute stack that makes training and serving large models possible.
Responsibilities
- Design and implement custom ML kernels (CUDA, CuTe, Triton) for core dLLM operations such as attention, matrix multiplication, gating, and normalization, optimized for modern GPU architectures.
- Design compute primitives to reduce memory bandwidth bottlenecks and improve kernel efficiency.
Nice to have
- Contribute to infrastructure stability and scalability, ensuring reproducibility, consistency across precision formats, and high utilization of compute resources.
- BS/MS/PhD in Computer Science, Engineering, or a related field (or equivalent experience).
- Proficiency in CUDA, CuTe, Triton, or other GPU programming frameworks.
- Understanding of ML frameworks (PyTorch, TensorFlow) from a systems perspective.
- Background in performance optimization and profiling of ML systems.
- Experience implementing low-precision formats (FP8, INT8, block floating point) or contributing to related compiler stacks (XLA, TVM).
- Familiarity with distributed training techniques (data parallel, model parallel, pipeline parallel).
- Proficiency in Python and at least one systems programming language (C++/Rust/Go).
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