Requirements:

• 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.
• Hands on experience with the post training phase of model training, with a strong emphasis on performance optimisation.

Nice to Haves:

• Paper at top-tier venues (such as NeurIPS, ICML, ICLR, AIStats, MLSys, JMLR, AAAI, Nature, COLING, ACL, EMNLP).

What You'll Be Doing:

• Design and write high-performant and scalable software for training models.
• Consistently post-train the models to reach SOTA level performance.
• Coordinate with other specialist teams (Agentic, Code…) to produce models that have strong all encompassing performance.
• Craft and implement techniques to improve the performance and results of our training cycles both on the SFT and the RL regime.
• Research, implement, and experiment with ideas on our supercompute and data infrastructure.
• Learn from and work with the best researchers in the field.

Perks and Benefits:

• A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.
• Full health and dental benefits, including a separate budget for mental health.
• RRSP matching, 401K, Pension Scheme.
• 100% Parental Leave top-up for up to 6 months, for either parent.
• Annual enrichment benefits:
  • Arts & culture, fitness/wellness, quality time, and a workspace improvement credit.
  • Education & learning stipend for conferences, courses, and coaching.
• 6 weeks of paid vacation (30 working days!)
• Budget for traveling to other offices if you are remote, plus an annual company offsite.