Experience managing GPU Kubernetes clusters with thousands of GPUs for ML or HPC workloads.
Proficient in debugging Linux, networking, and performance issues; familiarity with RDMA and NCCL is advantageous.
Skilled in Python or Go, with a preference for extending existing open-source projects.
Collaborated with researchers or ML engineers in cross-functional teams.
Demonstrated ability to identify bottlenecks and implement solutions in a fast-paced environment.
Responsibilities
Deploy and manage GPU Kubernetes clusters across multiple cloud environments.
Collaborate with cloud providers and hardware partners to enhance reliability and performance.
Automate fault detection and remediation for nodes, GPUs, and fabric to minimize human intervention.
Optimize fleet utilization and reduce downtime for faulty nodes.
Troubleshoot production failures and improve system operability.
Benefits
Weekly lunch stipend of $75/£75 or equivalent.
Comprehensive health and dental benefits, including a mental health budget.
RRSP matching, 401K, and Pension Scheme.
100% parental leave top-up for up to 6 months for any parent.
Annual enrichment benefits for arts, culture, fitness, and workspace improvements.
6 weeks of paid vacation (30 working days).
Budget for travel to other offices and an annual company offsite.
Full Job Description
What you will do
Deploy and operate GPU Kubernetes clusters across clouds, and bring up new hardware generations and providers.
Work with cloud providers and hardware partners on reliability, performance, and cost, including RDMA and high-speed interconnects.
Automate node, GPU, and fabric fault detection and remediation so most faults are fixed without a human.
Improve fleet utilization, track cost, and cut the time it takes to get a faulty node back into service.
Troubleshoot production failures and performance problems, and leave the system easier to operate than you found it.
We hire at more than one level. We set level based on the scope you've owned and how independently you drive work.
You may be a good fit if you have
Run GPU Kubernetes clusters with thousands of GPUs for ML or HPC workloads.
Debugged Linux, networking, and performance problems. Familiarity with RDMA, NCCL, or accelerator health is a plus.
Written software in Python or Go. You would rather extend a solid open-source project than rebuild it.
Worked with researchers, ML engineers, or another team whose goals were not identical to yours.
Found a bottleneck, proposed a fix, and driven it in a fast-moving environment.
If this does not line up exactly with your experience, we still encourage you to apply.
Full-Time Employees at Cohere enjoy these Perks:
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.
How and Where We Work:
Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening 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.
