Member Of Technical Staff (AI Infrastructure)

TL;DR

Member of Technical Staff (Performance Optimization): Building and optimizing high-performance infrastructure for generative AI inference with an accent on low-level GPU kernels, distributed systems, and compute efficiency. Focus on maximizing the performance of LLMs, VLMs, and video models through profiling, CUDA/Triton optimization, and co-designing hardware-aware model architectures.

Location: Must be based in or able to commute to San Mateo, CA

Salary: $175,000 - $220,000 USD (plus equity)

Company

A Series C, high-growth startup building the future of generative AI infrastructure, backed by top-tier venture firms.

What you will do

• Optimize GPU kernels and system performance for large-scale training and inference workloads.
• Analyze and resolve latency, throughput, and memory bottlenecks across the AI stack.
• Implement performance optimizations using CUDA, Triton, and advanced profiling tools.
• Collaborate with researchers to tune model architectures for maximum hardware efficiency.
• Scale inference and training systems within multi-GPU and multi-node environments.
• Maintain and improve benchmarking infrastructure to track execution speed and utilization.

Requirements

• Bachelor’s degree in Computer Science, Engineering, or equivalent practical experience.
• 5+ years of experience in performance optimization or high-performance computing.
• Proficiency in CUDA or ROCm with extensive experience using GPU profiling tools.
• Strong background in PyTorch and performance-critical model execution.
• Deep understanding of GPU architecture, parallel programming, and compute kernels.
• Proven ability to debug and optimize distributed systems in multi-GPU environments.

Nice to have

• Master’s or PhD in Computer Science or a related field.
• Experience optimizing LLMs, VLMs, or video models for production.
• Knowledge of ML compilers like torch.compile, Triton, or XLA.
• Background in hardware-aware model design and cloud-scale infrastructure (Kubernetes).

Culture & Benefits

• Meaningful equity participation in a rapidly growing, well-funded startup.
• Opportunity to solve high-impact, industry-leading challenges in AI infrastructure.
• Collaborative environment working alongside veterans from Meta and Google AI.
• Ownership of critical projects with direct influence on global AI deployment efficiency.
• Inclusive, innovation-focused culture with minimal bureaucracy.