Member of Technical Staff, GPU Infrastructure

Cohere

. Deploy and operate GPU Kubernetes clusters across clouds .

Posted 11/6/2026full-timeRemote • United States, CanadaLead💰 $270,000 - $335,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in deploying and operating GPU Kubernetes clusters, with a strong focus on performance optimization, fault detection, and collaboration with AI and ML teams. Proficient in troubleshooting and improving system operability in high-performance computing environments.

Highest-signal resume keywords

GPU Kubernetes Cluster ManagementLinux DebuggingPython Software DevelopmentRDMA FamiliarityPerformance Optimization

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

GPU Kubernetes ClustersLinux DebuggingPythonGoFault DetectionPerformance TroubleshootingCost TrackingOpen-Source Project ExtensionBottleneck IdentificationImplementation Driving

Soft Skills

CollaborationProblem-SolvingAdaptability

Tools & Technologies

NCCLHigh-Speed InterconnectsAI Research CollaborationML Engineering Collaboration

Industry Keywords

High-Performance ComputingMachine LearningCloud ProvidersHardware PartnersOn-Call Rotation

Tech Stack

Tools & technologies

CloudKubernetesLinuxNode.jsPythonGo

About the role

Key responsibilities & impact

Deploy and operate GPU Kubernetes clusters across clouds
Bring up new hardware generations and providers
Work with cloud providers and hardware partners on reliability, performance, and cost
Address RDMA and high-speed interconnects
Automate node, GPU, and fabric fault detection and remediation
Improve fleet utilization and track cost
Reduce the time required to return faulty nodes to service
Troubleshoot production failures and performance problems
Improve system operability
Collaborate with AI researchers and ML engineers on stability, scalability, and observability
Participate in a compensated 24x7 on-call rotation

Requirements

What you’ll need

Experience running GPU Kubernetes clusters with thousands of GPUs for ML or HPC workloads
Experience debugging Linux, networking, and performance problems
Familiarity with RDMA, NCCL, or accelerator health is a plus
Software development experience in Python or Go
Experience extending solid open-source projects
Experience working with researchers, ML engineers, or teams with differing goals
Experience identifying bottlenecks, proposing fixes, and driving implementation in a fast-moving environment
Availability for a compensated 24x7 on-call rotation
Must be authorized to work in the country of current residence
Must indicate whether work sponsorship is required now or in the future

Benefits

Comp & perks

A weekly lunch stipend of $75/£75 or equivalent in local currency
Full health and dental benefits
Separate mental health budget
RRSP matching
401K
Pension Scheme
100% parental leave top-up for up to 6 months, for either parent
Annual enrichment benefits for arts and culture, fitness/wellness, quality time, and workspace improvement
Education and learning stipend for conferences, courses, and coaching
6 weeks of paid vacation (30 working days)
Budget for traveling to other offices if remote
Annual company offsite
Co-working benefit for employees not near an office
$500 home office stipend
Daily lunch program, snacks, and regular community and social events for office-based employees