Build and maintain the high-performance, petabyte-scale data infrastructure that powers Cohere's AI model training and evaluation workloads.
Responsibilities
- ▹Build and maintain the high-performance data layer that Modeling teams rely on for training and evaluation jobs
- ▹Work directly on petabyte-scale storage infrastructure and its networking/performance challenges
- ▹Collaborate daily with researchers and engineers
Requirements
- ▹4+ years of experience with data storage infrastructure
- ▹Strong command of Python
- ▹Kubernetes experience, especially on the storage side (Persistent Volumes, CSI drivers, etc.)
- ▹Ability to transform unstructured data into performant datasets across storage backends such as S3, GCS and POSIX
- ▹Experience with distributed data processing frameworks such as Apache Beam, Spark or Flink
Nice to have
- ▹Familiarity with modern analytics tooling such as BigQuery, Airflow or dbt
- ▹Genuine excitement about AI, following the research with strong opinions
- ▹Comfort operating at the edge of what's known, building something new rather than optimizing what already exists
Soft skills
Curiosity about AI researchComfort with ambiguity and building new solutionsStrong cross-team collaboration
What we offer
- ▹Weekly lunch stipend ($75/£75 or local equivalent)
- ▹Full health and dental benefits, including a separate mental health budget
- ▹RRSP matching, 401(k), or pension scheme depending on location
- ▹100% parental leave top-up for up to 6 months, for either parent
- ▹Annual enrichment benefits (arts & culture, fitness/wellness, quality time, workspace improvement credit)
- ▹Education & learning stipend for conferences, courses and coaching
- ▹6 weeks of paid vacation (30 working days)
- ▹Travel budget to other offices for remote employees, plus an annual company offsite
- ▹$500 home office stipend, or a co-working benefit for those not near an office
About the company
Cohere is a leading security-first enterprise AI company that builds cutting-edge foundation models and end-to-end AI products for real-world business problems. The company is co-headquartered in Toronto and San Francisco, with additional offices in London, New York City, Montreal, Seoul, Germany and Paris.
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