Minimum qualifications:

• Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
• 10 years of experience with cloud native architecture in a customer-facing or support role.
• 5 years of experience with cloud infrastructure.
• 5 years of experience in a technical role focused on AI infrastructure or related areas
• Experience building and operationalizing machine learning models.
• Experience with GPU programming (e.g., CUDA, OpenCL) and optimization techniques.

Preferred qualifications:

• Experience with high-performance computing (HPC) environments and contributions to open-source projects related to AI or infrastructure.
• Experience training and fine-tuning large models (e.g., image, language, segmentation, recommendation, genomics) with accelerators.
• Experience with performance profiling tools (e.g., TensorFlow profiler, PyTorch profiler, Tensorboard).
• Experience designing/architecting large-scale infrastructure farms for specialist AI use cases.
• Experience with running MLPerf benchmarks, distributed training and optimizing performance versus costs.
• Excellent communication, presentation, and teamwork skills.