About the job
We are seeking an experienced AI Infrastructure Engineer to join our AI Incubation team. You will be focused on building and optimizing large-scale training infrastructure for Large Language Models (LLMs). The ideal candidate will combine engineering fundamentals with practical experience in AI infrastructure development, demonstrating both technical depth and the ability to deliver scalable solutions for complex AI systems.
Responsibilities
Designing and developing scalable AI infrastructure solutions for training and deploying large language models
Building and optimizing distributed training platforms using cutting-edge technologies
Implementing and maintaining containerized AI environments using Docker and Kubernetes
Optimizing CUDA kernels for maximum GPU utilization and performance
Developing platform software to support AI/ML workflows
Collaborating with AI researchers to implement efficient training and inference pipelines
Qualifications
Minimum
Have a bachelor's degree in Computer Science, Engineering, AI, Machine Learning, Distributed System or related field
5+ years of software engineering experience with focus on infrastructure and systems
Have expertise in GPU programming and CUDA optimization
Have experience with container technologies (Docker, Kubernetes), distributed systems and cloud computing
Demonstrate experience building large-scale distributed systems and optimizing neural network performance
Possess programming skills in Python, C++, and CUDA, with deep learning frameworks (PyTorch, Transformers)
Preferred
No preferred qualifications listed.