Software Engineer, GPU Infrastructure & Kubernetes (Remote) NEW

The Briefed; United States; Remote; USD 175,000 - 325,000; Full time

Benefits offered by this job

Lunch stipend

Health insurance

Dental cover

401(k)

Paid vacation

Learning stipend

Job summary

Cohere is hiring for an Internal Infrastructure role focused on running and expanding GPU Kubernetes fleets across clouds. You will work with researchers and ML engineers, diagnose Linux and networking issues, and write Python or Go code to automate tasks and improvements.

The role supports remote-friendly work in the United States, with a 24x7 on-call rotation and opportunities to optimize hardware, performance, and cost. Competitive salary and equity are offered along with health benefits.

Qualifications

• Ran GPU Kubernetes clusters with thousands of GPUs for ML or HPC workloads.
• Debugged Linux, networking and performance problems.
• Wrote software in Python or Go.
• Collaborated with researchers or ML engineers with different goals.

Responsibilities

• Deploy and run GPU Kubernetes clusters across clouds and bring up new hardware.
• Work with cloud providers and hardware partners on reliability, performance and cost, including RDMA.
• Automate fault detection and repair for nodes, GPUs and network fabric.
• Improve fleet use, track cost and shorten the time to return a faulty node.
• Join the paid 24x7 on-call rotation.

Skills

GPU Kubernetes

Linux debugging

Python

Go

Networking

Cloud platforms

Tools

RDMA

NCCL

Job description

Cohere builds foundation AI models for businesses. Its Internal Infrastructure team runs the shared Kubernetes fleets where Cohere's models are trained, evaluated and served: multi-cloud GPU and TPU clusters, node health and performance.

Key responsibilities

• Deploy and run GPU Kubernetes clusters across clouds, and bring up new hardware
• Work with cloud providers and hardware partners on reliability, performance and cost, including RDMA
• Automate fault detection and repair for nodes, GPUs and network fabric
• Improve fleet use, track cost and shorten the time to return a faulty node
• Join the paid 24x7 on-call rotation

Requirements

• Ran GPU Kubernetes clusters with thousands of GPUs for ML or HPC workloads
• Debugged Linux, networking and performance problems
• Writes software in Python or Go
• Worked with researchers or ML engineers whose goals differ from yours

Nice to have

• RDMA, NCCL or accelerator health monitoring

Remote details

• Remote-friendly; this posting is open in the United States
• A co-working benefit if you are not near an office, plus a $500 home office stipend

Salary and benefits

US base salary $175,000 to $325,000 a year, depending on location, plus equity. Benefits include a weekly $75 lunch stipend, full health and dental cover, 401(k), 6 weeks of paid vacation and a learning stipend.