Member of Technical Staff - Training Platform
Prime IntellectVisit Prime Intellect website
AI infrastructure company providing an integrated stack for training, evaluating, deploying, and continuously improving agentic models.
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Series ARecently funded34 current maintainers27 active leads7 new active leads9 lead step-downsTeam intelligence
Maintainer signals as of 9/25/2026
San Francisco, United States
Funding history
Projects
About Prime Intellect
Prime Intellect, Inc. operates AI infrastructure spanning RL environments, hosted training and evaluations, inference, secure sandboxes, and globally sourced GPU compute.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
Prime Intellect is hiring a Member of Technical Staff to develop hosted training infrastructure and platform experiences spanning Kubernetes orchestration, GPU scheduling, autoscaling, observability, backend services, monitoring tools, and frontend product interfaces.
Requirements
- Strong knowledge of open model families and fine-tuning techniques including LoRA, QLoRA, full fine-tuning, RLHF, and RLAIF
- Familiarity with inference engines such as vLLM, SGLang, and TensorRT-LLM
- Understanding of GPU hardware tradeoffs and distributed training fundamentals
- Strong Kubernetes operations experience with Helm, CRDs, operators, KEDA, gang scheduling, and GPU operators
- Production cluster debugging experience
- Cloud platform experience, preferably GCP
- Infrastructure automation experience with Helm, Terraform, and Ansible
- Observability experience with Prometheus, Grafana, Loki, OpenTelemetry, and DCGM
- Linux networking, namespaces, and performance tuning fundamentals
- Strong Python backend development with FastAPI, async programming, and SQLAlchemy
- Experience building Python agents that interact with Kubernetes APIs
- Modern frontend development with TypeScript, React or Next.js, Tailwind, and shadcn
- REST and tRPC API design experience
- Experience building developer tools, dashboards, and live-monitoring UIs
Responsibilities
- 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 that watch pods and synchronize cluster state
- Implement scheduling and autoscaling for heterogeneous GPU hardware
- Operate GitOps workflows and build model caches, checkpoint pipelines, and shared storage
- Operate observability systems and improve GPU cluster debugging
- Build job submission, live monitoring, logging, metrics, and model management surfaces
- Develop FastAPI backend services and REST APIs
- Build real-time monitoring and debugging tools
- Ship product interfaces with Next.js, React, and TypeScript
- Interface with trainers, inference servers, and environment servers
- Productize new training capabilities, model architectures, and reinforcement learning modes
Benefits
- Cash compensation of $150K–$300K
- Significant equity
- Flexible work arrangement with remote or San Francisco office options
- Full visa sponsorship
- Relocation support
- Professional development budget for courses and conferences
- Regular team off-sites
- Conference attendance
- Opportunity to shape decentralized AI development
