EDR are hiring Deep Learning engineers for a hyper-funded start-up within the ML/AI ecosystem who aim to bridge the gap between the ML/DL & Web3 community.

This is a rare point-in-time opportunity; perhaps even once in a lifetime. Our client offers the chance to work on one of the world’s most important technology problems whilst revolutionising against established political and corporate interests that control and price gouge it. Our client will allow machine learning engineers and researchers to train models at a higher scale, and lower cost, than AWS; achieved via a highly specialised deep learning compute protocol with minimal verification overhead.

Responsibilities include:

Build the offchain runtime – implement novel distributed ML methods in production Python code for use by ML researchers and engineers globally

Build the ML SDK – wrap ONNX, PyTorch, Tensorflow, Keras, and other frameworks in intuitive ways for minimal friction when training over the Gensyn network

Design decentralised monitoring systems – build logging and model training monitoring systems in a uniquely challenging decentralised environment

Write – contribute to technical reports / papers describing the system and discuss with the community

Minimum requirements:

Experience with distributed model training – have previously built training pipelines using data and model parallelism over distributed (ideally highly distributed) hardware

Passion for decentralisation – an understanding of web3 technologies and decentralised principles

Python experience – history of building production-level models and systems in Python

Nice to haves:

Publications in distributed ML/DL

Rust experience

Some knowledge of protocol engineering

What we offer:

Competitive salary + share of equity and token pool

Fully remote work

Quarterly, all expenses paid, company meet-ups around the world (Mexico is next)

28 paid holiday days per year

Whatever equipment you need

Paid sick leave

To find out more, please send your CV/Resume to david.ferguson@edr-gs.com and book a 1:1 consultation at calendly.com/david-ferguson-3 for a time that suits you best.