Staff Engineer, Inference Optimizations

🕒 October 31

🏄 California – Remote

🏄 California – Remote

💵 $191.2k - $239k / year

⏰ Full Time

🔴 Lead

🧑‍💻 Full-stack Engineer

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This company has sponsored H1B visas in the past.

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📋 Description

• Lead technical strategy for benchmarking and performance optimizations at inference engine and GPU kernel layers • Engineer solutions for attention-layer optimization, memory and precision management, and advanced parallelization across multi-node GPU clusters • Implement cutting-edge optimization techniques for generative AI infrastructure • Improve batch-size performance using AMD's AITER library for AMD MI355X, tuning CK or ASK for FP8/BF16 • Identify kernel-fusion opportunities for GLM-5 Transformer-block kernels, including FlashAttention and RMS Norm • Tune expert-gateway router kernels for MoE models such as Qwen3-235B, DeepSeek V3, and GLM-5 • Advise on modern NVIDIA and AMD GPU hardware procurement and software integration • Develop and deploy quantization techniques using FP8, INT8, and experimental FP4 • Provide technical mentorship through high-quality code and design reviews without direct management • Partner with Product Management and TPMs to translate hardware limits into shippable product features • Contribute to and integrate open-source AI while maintaining a presence in GPU infrastructure and model-performance communities

🎯 Requirements

• 5+ years of experience in high-performance computing or AI infrastructure • Proven track record of solving compute utilization and memory bandwidth bottlenecks • Deep familiarity with the Gen AI landscape, including LLM, VLM, and LMM model families • Hands-on experience with attention-layer optimizations and parallelization strategies across distributed GPU environments • Comprehensive understanding of NVIDIA and AMD GPU architectures and software ecosystems, including CUDA and ROCm • Extensive experience integrating, building with, and contributing to open-source software projects • Excellent system design skills related to low-level GPU programming, optimization, memory access patterns, and parallel execution • Experience acting as a technical lead and driving design and delivery through cross-functional alignment and expert-level delegation • Deep understanding of GPU architectures, including SMs, warp scheduling, and Tensor Cores • Expert-level Triton or CUDA proficiency • Experience contributing to the Triton compiler or writing custom CUDA kernels for a major LLM is desired by the posting's wording

🏖️ Benefits

• Reimbursement for relevant conferences, training, and education, subject to company policy • Flexible time off • Local team meetups • Mental health and well-being support • Annual bonus plan eligibility for non-sales roles, subject to plan terms and local eligibility • Potential new hire equity grant, subject to plan terms and local eligibility • Employee Stock Purchase Program opportunity in participating countries, subject to eligibility • Comprehensive total rewards package • Professional development resources and career development support

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