Infrastructure engineers who have run GPU clusters at the world's most demanding AI organizations.
Chief Executive Officer & Co-Founder
Before founding Deepiix, Anna served as VP of Infrastructure at OpenAI, where she oversaw the GPU cluster infrastructure powering GPT-4, DALL-E 3, and Sora training. Her team managed thousands of A100s and was responsible for the scheduling systems that delivered OpenAI's training efficiency gains. Prior to OpenAI, Anna earned her PhD in Distributed Systems from ETH Zurich, where her dissertation focused on fault-tolerant distributed training algorithms. She brings a rare combination of deep academic grounding and large-scale production experience to Deepiix's technical direction.
Chief Technology Officer & Co-Founder
Ryan spent eight years at NVIDIA's Developer Technology group, working directly with the world's largest AI labs to optimize their deep learning training workloads on CUDA. As a recognized CUDA optimization expert, he contributed to the cuDNN library and co-authored three patents on GPU memory management. At NVIDIA, Ryan personally tuned training kernels for GPT-3, PaLM, and early diffusion model training systems. His kernel work is embedded in Deepiix's core optimization layer, delivering performance that cannot be achieved through standard PyTorch or TensorFlow abstractions alone.
VP Platform Engineering & Co-Founder
Mei architected ByteDance's internal ML training platform, which at peak operated over 10,000 daily training jobs serving TikTok's recommendation and content understanding systems. Her platform reduced ByteDance's GPU cluster idle time from 38% to 7% through hierarchical scheduling and workload prediction models. Mei brings exceptional systems engineering discipline to Deepiix — her team owns the scheduler, the distributed checkpoint system, and the real-time monitoring infrastructure that underpins the entire platform.
We are building a small, exceptional team of GPU infrastructure engineers. If you have worked on serious training systems, we want to hear from you.
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