AI/ML Solution Architect

In this role as a Solution Architect specializing in GPU/TPU Kernel Optimization, your main responsibility will be to design and optimize high-performance kernels for cutting-edge Machine Learning operations. You will work on redefining performance boundaries across massive training runs and high-speed inference workloads, while also shaping the developer infrastructure that powers next-generation AI systems. Key Responsibilities: - Design and optimize high-performance kernels using languages like Pallas, Mosaic, and Triton targeting TPU and GPU architectures for critical Machine Learning operations. - Architect infrastructure such as benchmarking suites, autotuning frameworks, performance analysis tools, regression testing, and documentation. - Transform the developer community's interaction with custom kernels in key Open-Source Software libraries. - Stay updated on the latest advancements in hardware architectures, compiler technologies, and AI models to identify new opportunities for performance optimization. - Engage with ML researchers, framework developers (JAX, PyTorch), and compiler engineers (XLA) to enhance adoption. - Identify new requirements and address bottlenecks by providing appropriate solutions. Qualifications Required: - 12-18 years of experience in software development. - Expertise in optimizing TPU/GPU code using low-level kernel languages like Pallas, CUDA, or Triton. - Knowledge of ML Frameworks (JAX/PyTorch), common operations like attention and Mixture of Experts (MoEs), including model optimization and low-precision formats. - Understanding of modern accelerators (data movement, pipelining, heterogeneous compute, and scale-out). - Understanding of compiler principles (optimization, code generation) and toolchains such as MLIR, OpenXLA. - Showcase of building developer infrastructure, including Open-Source Software libraries, flexible high-performance APIs, and easy-to-consume documentation. - Excellent investigative and problem-solving capabilities with communication skills across cross-functional teams. In this role as a Solution Architect specializing in GPU/TPU Kernel Optimization, your main responsibility will be to design and optimize high-performance kernels for cutting-edge Machine Learning operations. You will work on redefining performance boundaries across massive training runs and high-speed inference workloads, while also shaping the developer infrastructure that powers next-generation AI systems. Key Responsibilities: - Design and optimize high-performance kernels using languages like Pallas, Mosaic, and Triton targeting TPU and GPU architectures for critical Machine Learning operations. - Architect infrastructure such as benchmarking suites, autotuning frameworks, performance analysis tools, regression testing, and documentation. - Transform the developer community's interaction with custom kernels in key Open-Source Software libraries. - Stay updated on the latest advancements in hardware architectures, compiler technologies, and AI models to identify new opportunities for performance optimization. - Engage with ML researchers, framework developers (JAX, PyTorch), and compiler engineers (XLA) to enhance adoption. - Identify new requirements and address bottlenecks by providing appropriate solutions. Qualifications Required: - 12-18 years of experience in software development. - Expertise in optimizing TPU/GPU code using low-level kernel languages like Pallas, CUDA, or Triton. - Knowledge of ML Frameworks (JAX/PyTorch), common operations like attention and Mixture of Experts (MoEs), including model optimization and low-precision formats. - Understanding of modern accelerators (data movement, pipelining, heterogeneous compute, and scale-out). - Understanding of compiler principles (optimization, code generation) and toolchains such as MLIR, OpenXLA. - Showcase of building developer infrastructure, including Open-Source Software libraries, flexible high-performance APIs, and easy-to-consume documentation. - Excellent investigative and problem-solving capabilities with communication skills across cross-functional teams.