Member of Technical Staff, Training Infra Engineer

Who are we?

Role Overview

Contribute in and provide strong support for model training pipelines, ship state of the art models to production, and bridge the gap between research and production. We have one of the highest ratio of compute to engineers in the world. We do not delineate strongly between engineering and research. Everyone will contribute to writing production code and supporting our research effort depending on individual interest and organizational needs. We have all the compute, data, and talent available for you to do your best work.

Please Note: We have offices in London, Paris, Toronto, San Francisco and New York but also embrace being remote-friendly! There are no restrictions on where you can be located for this role.

Key

Responsibilities

• Design and write high-performant and scalable software for training.
• Improve our training setup from an infrastructure and codebase performance standpoint.
• Craft and implement tools to speed up our training cycles and improve the overall efficacy of our training infrastructure
• Research, implement, and experiment with ideas on our supercompute and data infrastructure.
• Learn from and work with the best researchers in the field.

Qualifications

• Extremely strong software engineering skills.
• Proficiency in Python and related ML frameworks such as JAX, Pytorch and XLA/MLIR.
• Experience with distributed training infrastructures (Kubernetes, Slurm) and associated frameworks (Ray)
• Experience using large-scale distributed training strategies.
• Hands on experience on training large model at scale and having contributed to the tooling and/or setup of the training infrastructure
• Bonus : paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

Working Location

This role can be based remotely or from one of our office locations listed on the job description - there is no minimum in-office qualification requirement. We care most about hiring exceptional people regardless of locations, though please check the location listed on the posting for guidance around the core time zone or working hours alignment expected for the role.