Cohere에서 대규모 모델 학습 인프라를 설계하고 최적화할 Member of Technical Staff를 채용합니다. Python, JAX/PyTorch, 분산 학습 인프라(Kubernetes, Slurm, Ray)에 대한 깊은 이해와 실무 경험이 필수입니다. 연구와 프로덕션의 경계 없이 최첨단 AI 모델을 구축하는 환경에서 최고의 동료들과 함께 성장할 수 있습니다.
Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.
We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.
We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.
We are a global technology company co-headquartered in Toronto and San Francisco, with key offices in London, New York City, Montreal, Seoul, Germany and Paris. Join us!
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.
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.
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).
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.
Cohere is remote-friendly. We have offices in Toronto, San Francisco, New York City, London, Paris, Montreal, and more coming soon.
For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
For those not near an office: a co-working benefit so you can work alongside others in your city.
Everyone receives a $500 home office stipend to set up your workspace properly.
If any of the above doesn’t line up exactly with your experience, we still encourage you to apply.
We strive to create an inclusive work environment for all; we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, please submit an Accommodations Request Form, and we will work together to meet your needs.
We may use AI-enabled tools to screen and assess applicants against the criteria for this position. This helps our recruiters identify potentially qualified candidates, but it doesn't limit the applications our recruiters may review or consider.
