Wafer Verified
Digital Health, Healthtech, Software Development, Mobile Applications
Member Of Technical Staff (Summer Intern)
San Francisco, California, United StatesOnsiteInternshipStaff$6,000–$10,000 /yrPosted 2 months agoHidden Gem · YC Startup
Role summary
Join a team focused on building the future of inference, GPU optimization, and AI infrastructure. This internship offers the opportunity to directly influence technical direction and develop core systems for a GPU optimization platform. Responsibilities include building scalable infrastructure for AI model training and inference, and contributing to technical decisions and architecture choices.
Join our team to build the future of inference, GPU optimization and AI infrastructure. You'll work directly with the team to define our technical direction and build the core systems that power our GPU optimization platform.
### **What You'll Do**
* Build scalable infrastructure for AI model training and inference
* Lead technical decisions and architecture choices
### **What We Look For**
#### **Core Technical Expertise**
* GPU Fundamentals: Deep understanding of GPU architectures, CUDA programming, and parallel computing patterns.
* Deep Learning Frameworks: Proficiency in PyTorch, TensorFlow, or JAX, particularly for GPU-accelerated workloads.
* LLM/AI Knowledge: Strong grounding in large language models (training, fine-tuning, prompting, evaluation).
* Systems Engineering: Proficiency in C++, Python, and possibly Rust/Go for building tooling around CUDA.
### **What You'll Do**
* Build scalable infrastructure for AI model training and inference
* Lead technical decisions and architecture choices
### **What We Look For**
#### **Core Technical Expertise**
* GPU Fundamentals: Deep understanding of GPU architectures, CUDA programming, and parallel computing patterns.
* Deep Learning Frameworks: Proficiency in PyTorch, TensorFlow, or JAX, particularly for GPU-accelerated workloads.
* LLM/AI Knowledge: Strong grounding in large language models (training, fine-tuning, prompting, evaluation).
* Systems Engineering: Proficiency in C++, Python, and possibly Rust/Go for building tooling around CUDA.