Solution Architect - Core ML Frameworks, Kernels & Performance

Responsibilities

• Design and optimize high-performance kernels (using languages like Pallas, Mosaic, and Triton) targeting Tensor Processing Unit (TPU) and Graphics Processing Unit (GPU) architectures for critical Machine Learning (ML) operations, redefining what’s possible from massive training runs to high-speed inference
• Architect infrastructure such as benchmarking suites, autotuning frameworks, performance analysis tools, regression testing, and documentation, transforming how the developer community interacts with increasingly critical custom kernels in key Open-Source Software (OSS) libraries
• Track the latest advancements in hardware architectures, compiler technologies, and AI models to identify new opportunities for performance optimization through custom kernels
• Engage with ML researchers, framework developers (Just After eXecution (JAX), PyTorch), and compiler engineers (Accelerated Linear Algebra (XLA)) to enhance adoption, identify new requirements, and address bottlenecks by providing appropriate solutions

Languages