Machine Learning GPU Engineer, Gensyn

• Background in relevant theory - i.e. computer science, machine learning, algorithms, distributed systems
• Deep understanding of computational bottlenecks - experience working with low-level computer science principles (e.g. determinism vs non-determinism, floating point implementations, efficient data structures etc..)
• Passion for decentralisation - an understanding of web3 technologies and decentralised principles
• Low-level HW experience - Have worked directly on/with ML hardware (GPUs, TPUs, IPUs, etc..)

Desirable

• Research novel ML verification - work with determinism, game theory, optimisation theory, and more to design low-redundancy ML verification mechanisms; with a focus on making certain results reproducible across heterogenous hardware
• Work with cutting-edge ML frameworks - fork and modify existing ML frameworks and low-level libraries (e.g. CUDA, OpenCL) to build a new way of performing ML computations
• Build the offchain runtime - implement newly proposed techniques for the above in constrained environments in production code for use by ML researchers, engineers, and academics globally
• Write & engage - contribute to technical reports/papers describing the system and discuss with the community