Systems Performance Engineer

1 week ago


India Phinity Full time

We want to enable AI to bootstrap its own intelligence, to discover new computational paradigms. 5% improvements in FlashAttention, we're building the infrastructure that will enable every AI model to optimize its own compute stack. Of course, to automate algorithm and hardware discovery, we need to break the data barrier. CUDA is a low-resource language, and kernel optimization depends a lot on context and hardware that models simply are not trained on. Phinity is building the canonical training data infrastructure that will enable agentic hardware engineering and optimization, which will fuel algorithmic discovery. We are building environments for agents to learn to write kernel from a spec and optimize them on specific hardware, and eventually, to discover new hardware breakthroughs. We're seeking top engineers for a contractor role who can optimize hardware for model training and inference workloads, who can bake their industry experience into a model. This is a hybrid Systems Engineer/AI research role where you will be looking through and debugging model reasoning traces and designing the optimal CUDA problems to teach unreleased models to automate your work in industry. Languages: CUDA, C++, Python, Frameworks: JAX/XLA, PyTorch, TensorFlow (at the C++ level), Pallas Compiler Tools: NVCC, PTX assembly, MLIR/XLA understanding Optimized attention, GEMM, or convolution at the assembly level ~



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