14 hours ago
London, United KingdomSenior
Responsibilities
- Design, build, and operate distributed storage systems for model-training and evaluation workloads.
- Run stateful storage systems across Kubernetes clusters at petabyte scale.
- Collaborate with researchers and training-infrastructure teams to define throughput, latency, and durability requirements.
- Solve networking, I/O, consistency, and cross-region data-movement problems involving large datasets and model checkpoints.
Requirements
- Strong fundamentals in storage, including replication, consistency, caching, and data lifecycle management.
- Strong coding ability in Python or Go, with willingness to learn the other language.
- Experience running stateful systems on Kubernetes, including Persistent Volumes, CSI drivers, and StatefulSets.
- Hands-on experience with S3 or similar cloud object storage and POSIX-style filesystems.
- Experience with parallel or HPC filesystems such as Weka, VAST, or Lustre is a bonus.
- Familiarity with data-loading and checkpointing patterns in large-scale model training is a bonus.
Benefits
- Weekly lunch stipend of $75/£75 or local equivalent.
- Full health and dental benefits, including a separate mental-health budget.
- RRSP matching, 401K, or pension scheme, depending on location.
- 100% parental-leave top-up for up to six months for either parent.
- Annual enrichment benefits covering arts and culture, fitness and wellness, quality time, and workspace improvements.
- Education and learning stipend for conferences, courses, and coaching.
- Six weeks of paid vacation, or 30 working days.
- Travel budget for remote employees visiting other offices and an annual company offsite.
- Remote-friendly work arrangement with offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin, and Seoul.
- Daily lunch program, snacks, and community events for office employees.
- Co-working benefit for employees not near an office.
- $500 home-office stipend.
Tech Stack
Categories
BackendData Engineering
About Cohere
Cohere builds large language models and an enterprise AI platform that companies use for search, summarization, and workflow automation, delivered via API or private deployments. Founded in 2019 and headquartered in Toronto, it focuses on multilingual models, data controls, and options to run across major clouds or on-premises. The business is privately held and serves security- and compliance-sensitive organizations.