Our Client Currently looking for Principal Engineer – GPU Driver & System Software

Roles And Responsibilities:-

• API Layer: Architect, develop, and optimize features for industry-standard APIs including Vulkan, DirectX, OpenGL ES, and OpenCL.
• Kernel & Firmware: Work deep in kernel-mode drivers and GPU firmware to improve hardware control, stability, scheduling, memory management, and execution efficiency.
• Performance: Identify, analyze, and eliminate bottlenecks across the stack — including driver overhead, memory bandwidth, GPU scheduling, compute throughput, and power/performance tradeoffs.
• Architecture Collaboration: Partner closely with Architecture, Micro-architecture, Compiler, and GPU Model teams to influence next-generation GPU design and ensure the software stack fully leverages the hardware.
• Technical Leadership: Lead complex debug efforts, guide design decisions, mentor engineers, and help raise the technical bar across the GPU driver team.
• No Silos: You are not restricted to only the API layer, kernel driver, firmware, or performance. You can work across the entire GPU software stack.
• Shape the Hardware: Your software insights will directly influence next-generation GPU architecture and micro-architecture.
• High-Impact Work: Your contributions will help turn silicon capability into real-world graphics, compute, and AI performance.

Requirements

• Experience of building GPU drivers, graphics systems, or low-level systems software.
• You are fluent in C/C++ and comfortable working close to hardware.
• You have deep expertise in one or more industry-standard APIs such as Vulkan, DirectX 12, OpenCL, or OpenGL ES.
• You understand GPU internals at a deep level, including memory hierarchies, command submission, scheduling, synchronization, pipeline architecture, and performance bottlenecks.
• You enjoy working across boundaries — from API design to kernel drivers, firmware, compiler interaction, and hardware architecture.

Preferred Qualifications (Nice to Have)

• Background in GPU performance analysis, firmware, virtualization, compiler, or runtime optimization for GPUs or accelerators.
• Familiarity with ML/AI workloads, DNN operators and their mapping onto GPU or accelerator architectures.
• Experience collaborating with architects, micro-architects, compiler, and model teams.

• Are you interested in this position?

   

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