GPU software Engineer/Architect

Triune Infomatics Inc is seeking a GPU Software Engineer/Architect for a GPU software integration project supporting Samsung Cognos. The role focuses on developing and integrating GPU and AI software on AMD platforms, contributing to open-source projects, and delivering performance benchmarks and technical documentation.

Responsibilities:

• Design and develop GPU software modules aligned with project milestones
• Perform systems integration and end-to-end testing of AI stack SW modules
• Validate AMD Infinity Bridge and AIS on MI210 GPU hardware
• Conduct functional and performance benchmarking (pSLC Firmware, CXL, ROCm)
• Implement and validate SGLang changes for L3 to L1 memory transfer optimization
• Develop and contribute CaMa module changes to the ROCm software stack
• Collaborate with the SGLang open-source community and contribute code to their public GitHub repo
• Develop CaMa module for ROCm over Infinity Fabric/Ethernet
• Perform E2E performance benchmarking and publish formal benchmarking reports
• Integrate CaMa changes into the Cognos AI stack and publish integration documentation
• Scope UALink support for CaMa and publish an investigation/feasibility document
• Maintain all documentation, code, and status updates in Confluence, Jira, and GitHub/GitLab

Requirements:

• Hands-on experience with AMD GPU platforms, specifically MI210
• Proficiency with AMD ROCm software stack including kernel libraries and drivers
• Experience with AMD Infinity Bridge / Infinity Fabric architecture
• Familiarity with CXL (Compute Express Link) memory integration
• Experience with NVMe storage and GPU Direct Storage (GDS)
• Experience with SGLang or similar LLM inference frameworks
• Familiarity with AI stack installation and end-to-end workload benchmarking
• Knowledge of GPU memory hierarchy (HBM, L1/L3 cache) and data transfer optimization
• Proficiency in GPU kernel programming and library management (e.g., GDS, CaMa)
• Strong proficiency in C/C++ and Python for GPU/systems-level development
• Experience with open-source contribution workflows (GitHub, pull requests, code reviews)
• Familiarity with Jira and Confluence for project management and documentation
• Experience with pSLC firmware validation and performance benchmarking methodologies
• Ability to work independently and deliver against defined monthly milestones
• Strong written communication skills for publishing technical reports and documentation
• Collaborative mindset; ability to work with third-party teams (AMD, SGLang community)
• Prior experience with Samsung Cognos AI stack or similar enterprise AI platforms
• Familiarity with UALink protocol and its GPU interconnect applications
• Prior open-source contributions to ROCm, SGLang, or similar GPU frameworks
• Experience presenting benchmarking results to semiconductor partners (AMD, NVIDIA, etc.)