Member of Technical Staff - AI Training Platform

Unconventional AI is developing energy-efficient computing technology to support the next generation of artificial intelligence. The Member of Technical Staff will build and scale the infrastructure, tooling, and optimization systems used to train, evaluate, benchmark, and deploy models on novel hardware.

Responsibilities:

• Architect, scale, and maintain the core AI/ML/RL training platform and infrastructure. Design and scale multi-node distributed training systems, implementing elastic sharding and robust data streaming pipelines for fast, large-scale iteration. Implement and robust model checkpointing and recovery mechanisms
• Maintain and expand our proprietary training framework, ensuring it provides a robust and flexible foundation for all internal model training
• Develop and optimize kernels using low-level programming models like CUDA and Triton. Design rigorous benchmarking suites to track Model Flops Utilization (MFU), memory bandwidth, and convergence stability
• Build and iterate on tooling to enable rapid, high-level evaluation of novel hardware ideas against benchmarks
• Act as a translator, discussing algorithmic trade-offs with theorists and converting model requirements into concrete specifications for infrastructure and hardware engineering teams
• Design systems to track and visualize quality-vs-efficiency Pareto frontiers, enabling researchers to optimize models for both performance and energy consumption