California: eligible, according to the employer's posting.
Who can apply: Only open to applicants in: California.
Location as listed by the employer: “North America Remote / San Francisco, CA”
Apply on Andromeda's site ↗
Opens the employer's official application page.
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About this role
Andromeda is hiring for a Forward Deployed Engineer - SRE role (full-time). See the official posting for full details.
Requirements
- Hands-on experience operating GPU clusters in production (NVIDIA A100/H100/H200/B200 or equivalent). You understand GPU memory hierarchies, ECC behavior, thermal throttling, and hardware failure modes from direct experi…
- Production experience with InfiniBand, RoCE, or NVLink fabrics in the context of distributed training. You can diagnose why an all-reduce is slow, identify a degraded link in a fat-tree topology, and reason about conges…
- Working knowledge of how large training and inference jobs actually run. You don't need to design models, but you need to understand what's happening at the systems level when a large run stalls.
- Expert-level Linux experience: kernel tuning, driver management (NVIDIA drivers, CUDA toolkit), cgroup/namespace internals, container runtimes, and performance profiling at the syscall and hardware level.
- Strong experience running Kubernetes in production with GPU workloads. Experience with device plugins, topology-aware scheduling, multi-cluster, custom operators. Experience with Slurm or other HPC schedulers is equally…
- Strong engineering skills in Python, Go, or Bash. You build production-grade tools and services, not just scripts.
- Infrastructure-as-Code proficiency (Terraform, Helm, Ansible, or equivalent).
- Hands-on experience building monitoring and alerting for GPU-specific telemetry (DCGM, nvidia-smi, fabric manager metrics) integrated into actionable dashboards.
Summarized from the employer's posting — check the full posting for every requirement.
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