Performance Engineer (AI)

TL;DR

Performance Engineer (AI): Architecting and implementing foundational GPU performance systems to power large language models with an accent on maximizing GPU utilization, custom kernel development, and distributed system architectures. Focus on designing and optimizing GPU kernels, orchestrating multi-node GPU clusters, and improving inference efficiency at scale.

Location: Hybrid with at least 25% in-office presence in San Francisco

Salary: $315,000 - $560,000 USD annually

Company

hirify.global is a public benefit corporation focused on creating reliable, interpretable, and steerable AI systems with a collaborative and impact-driven research culture.

What you will do

• Architect and implement GPU performance optimizations for large language models
• Develop custom kernels and optimize tensor core usage
• Design distributed communication strategies for multi-node GPU clusters
• Optimize training and inference pipelines for AI models
• Build performance modeling frameworks to predict and improve GPU utilization
• Collaborate with hardware vendors to influence future accelerator capabilities

Requirements

• Must have at least a Bachelor's degree or equivalent experience
• Hybrid work format with minimum 25% office presence
• Visa sponsorship available but not guaranteed for all candidates
• Deep experience with GPU programming and optimization at scale
• Strong knowledge of CUDA, Triton, CUTLASS, and ML frameworks like PyTorch and JAX
• Experience with distributed systems and performance engineering

Nice to have

• Experience with low-precision quantization techniques (INT8/FP8)
• Familiarity with kernel fusion and memory bandwidth optimization
• Background in large-scale training infrastructure and fault tolerance

Culture & Benefits

• Competitive compensation including equity and benefits
• Generous vacation and parental leave
• Flexible working hours
• Collaborative office environment in San Francisco
• Commitment to diversity and inclusion