Member of Technical Staff - Training Platform

The role

You will help build a hosted training platform that allows users to launch LoRA and full fine-tuning runs on managed GPU clusters. The role involves developing developer-facing surfaces and the underlying Kubernetes-based training infrastructure.

What you will do

• Design and operate Kubernetes-based training and inference orchestration across multi-cluster, multi-cloud GPU fleets
• Build and maintain Helm charts for reproducible Training stacks
• Develop Python control-plane agents to watch pods and report run state
• Implement scheduling and autoscaling for heterogeneous hardware using KEDA, LeaderWorkerSet, taints/tolerations, and gang scheduling
• Run a GitOps workflow using PRs, Helm values, and CI
• Build node-local model caches, checkpoint pipelines, and shared storage
• Operate the observability stack including Prometheus, Grafana, Loki, and DCGM
• Build developer-facing surfaces for job submission, monitoring, logs, metrics, and model management
• Develop FastAPI backend services and REST APIs
• Ship product UI in Next.js, React, TypeScript, shadcn, Tailwind, tRPC, and TanStack Query

Required qualifications

• Strong working knowledge of the modern AI stack including open model families, finetuning techniques, and inference engines
• Familiarity with GPU hardware tradeoffs
• Understanding of distributed training fundamentals
• Awareness of frontier models, training methods, and infra patterns
• Strong Kubernetes operations experience including Helm, CRDs, operators, KEDA, gang scheduling, and GPU operator
• Comfortable debugging real production clusters
• Cloud platform experience
• Infrastructure automation experience with Helm, Terraform, or Ansible
• Observability experience with Prometheus, Grafana, Loki, OpenTelemetry, or DCGM
• Linux fundamentals including networking, namespaces, and performance tuning
• Strong Python backend development with FastAPI, async, and SQLAlchemy
• Comfortable building Python control-plane agents that talk to Kubernetes APIs

Nice to have

• GCP preferred (GCS, GKE, Cloud Run, Cloud Tasks)

Benefits

• Cash compensation $150K–$300K with significant equity
• Flexible work arrangement (remote or San Francisco office)
• Full visa sponsorship and relocation support
• Professional development budget for courses and conferences
• Regular team off-sites and conference attendance

About the company

Prime Intellect is building the open superintelligence stack, providing infrastructure for frontier AI labs. The company has raised $150M in total funding from various investors including Founders Fund, Radical Ventures, and NVIDIA.