2mo ago

Member of Technical Staff - Inference

United States·San Franciscofull-timelead

OtherMember Of Technical Staff

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Quick Summary

Key Responsibilities

Build a multi-tenant LLM serving platform that operates across our cloud GPU fleets. GPU‑Aware Scheduling: Design placement and scheduling algorithms for heterogeneous accelerators.

Requirements Summary

3+ years building and running large‑scale ML/LLM services with clear latency/availability SLOs. Inference Backends: Hands‑on with at least one of vLLM, SGLang, TensorRT‑LLM.

Technical Tools

OtherMember Of Technical Staff

Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.

Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.

Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.

This is a hybrid position spanning cloud LLM serving, LLM inference optimization and RL systems. You will be working on advancing our ability to evaluate and serve models trained with our RL Lab at scale. The two key areas are:

Building the infrastructure to serve LLMs efficiently at scale.
Optimization and integration of inference systems into our RL training stack.

Responsibilities

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Requirements

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Nice to Have

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Data & Observability: Kafka/PubSub, Redis, gRPC/Protobuf; Prometheus/Grafana, OpenTelemetry; reliability patterns.

Infra & Config Automation: Terraform/Ansible, infrastructure-as-code, reproducible environments

Open Source: Contributions to serving, inference, or RL infrastructure projects.

What We Offer

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✓Cash Compensation Range of $150-300k with significant equity incentives

✓Flexible work arrangement (remote or San Francisco office)

✓Full visa sponsorship and relocation support

✓Professional development budget

✓Regular team off-sites and conference attendance

✓Opportunity to shape decentralized AI and RL at Prime Intellect

You'll join a team of experienced engineers and researchers working on cutting-edge problems in AI infrastructure. We believe in open development and encourage team members to contribute to the broader AI community through research and open-source contributions.

We value potential over perfection. If you're passionate about democratizing AI development, we want to talk to you.

Ready to help shape the future of AI? Apply now and join us in our mission to make powerful AI models accessible to everyone.