Machine Learning GPU Engineer

Job Description

Gensyn is the hyperscale, cost-efficient compute protocol for the world’s deep learning models.


  • 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


  • 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..)


  • Competitive salary + share of equity and token pool