Cohere
Software Engineer, Data Infrastructure
About this role
Cohere seeks a Software Engineer to design and operate a distributed petabyte-scale storage system that feeds model training workloads across Kubernetes clusters. You'll solve complex data movement, networking, and consistency challenges while collaborating with researchers to optimize GPU utilization and training performance.
What you'll do
- Design and build distributed storage infrastructure for model training at petabyte scale
- Operate stateful systems on Kubernetes clusters with focus on performance and reliability
- Collaborate with researchers and training teams to define throughput, latency, and durability requirements
- Solve networking, I/O, and consistency challenges for cross-region data movement
- Optimize data loading and checkpoint patterns to minimize GPU idle time
- Manage data lifecycle across cloud object storage and POSIX filesystems
What they're looking for
- Distributed storage systems and replication
- Python or Go programming
- Kubernetes and stateful workloads (Persistent Volumes, CSI drivers, StatefulSets)
- Cloud object storage (S3)
- POSIX filesystem experience
- Data consistency and caching strategies
- HPC or parallel filesystems (preferred)
- Large-scale model training workload understanding (preferred)
Benefits
- $75/£75 weekly lunch stipend
- Full health, dental, and mental health benefits
- 100% parental leave top-up for up to 6 months
- 6 weeks paid vacation (30 working days)
- RRSP matching, 401K, or Pension Scheme
- Annual enrichment stipend for education, arts, fitness, and workspace improvements
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Cohere
Cohere builds enterprise AI systems and large language model infrastructure, including audio inference optimization, agentic AI workflows, and petabyte-scale data infrastructure for model training. The company is hiring software engineers, infrastructure specialists, forward-deployed engineers to work with enterprise customers, and IT support staff.
- Website
- cohere.com
Likely interview questions
- Walk us through your experience designing or operating distributed storage systems at scale—what were the key consistency and replication challenges?
- Tell us about a time you optimized data access patterns for compute-intensive workloads; how did you measure success?