GPU Engineer

Key Responsibilities: Develop high-performance GPU kernels for specialized hardware platforms using PyTorch and Triton frameworksBuild software solutions leveraging custom compiler toolchains and SDK capabilitiesDesign and implement kernel-level optimizations to control and improve hardware execution behaviorPort and optimize open-source AI/ML models for proprietary or custom SDK environmentsAdapt and run high-performance computing benchmarks and stress workloads, including: High Performance Linpack (HPL)BERT and similar benchmark-style workloadsDevelop stress testing and validation workloads aligned with hardware behavior and platform reliability goalsSupport validation and performance testing for both current and next-generation hardware platformsCollaborate closely with platform architects, compiler teams, and system engineers to enhance end-to-end system performanceCore Technical Skills (Must-Have) Programming & FrameworksStrong proficiency in PythonExpertise in C/C++ for systems-level programmingHands-on experience with PyTorchExperience with Triton (kernel development and Triton language)GPU & Systems ExpertiseMandatory experience in GPU kernel developmentStrong understanding of GPU architecture and performance optimization techniquesExperience with compiler optimizations and runtime execution modelsFamiliarity with custom SDKs and hardware abstraction layersPerformance & WorkloadsHands-on experience in: GEMM (matrix multiplication) kernel developmentPorting and optimizing ML models on new/custom hardware platformsSystem-level performance tuning, benchmarking, and stress testing