Magic is working on frontier-scale code models to build a coworker, not just a copilot.
Things we believe
- Code generation is both a product and a path to AGI
- AGI safety matters and is solvable
- To build a great AI product, we need to train our own frontier-scale model
- Transformers aren’t the final architecture; we have something with a multi-million-token context window
Things we do
- Stare at PTX and SASS to optimize GPU kernels
- Keep Kubernetes clusters with thousands of GPUs busy and stable
- Scour every corner of the internet for data
- Adapt our sharding framework to train a new architecture
- Design new hardware-aware algorithms
Why work on ML at Magic?
- We care a lot
- You will work on really hard problems
- We’ve raised $145 million from Nat Friedman, Daniel Gross, CapitalG (Alphabet), and Elad Gil
- We have thousands of GPUs
If this sounds exciting, come join our team or get on the waitlist!
