Train, deploy, and continuously improve your own models on an integrated compute, training, inference, and sandbox stack. Backed by Menlo.
About the role
Compute is the foundational input of everything Prime Intellect does — and right now, the picture of our compute supply, demand, and economics lives across spreadsheets, partner conversations, and people's heads. This role changes that.
What they're looking for
- 3–7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles where you've built data infrastructure that served real business outcomes
- Strong technical skills: comfortable building and maintaining data warehouses, writing production-quality pipelines (Python, SQL), modeling data (dbt or equivalent), and connecting disparate systems via APIs
- Experience with modern data stack tooling — Snowflake / BigQuery / Databricks, dbt, orchestration (Airflow, Dagster, etc.), and BI/dashboarding tools
- A builder's instinct paired with business judgment — you don't just build what's asked, you understand the business well enough to build the right thing
- Comfortable being the data backbone for cross-functional teams — translating between business needs and the systems that serve them
- Familiarity with modern AI tooling and an interest in building AI-accessible data layers (natural-language querying, LLM-powered analytics) that let non-technical teams self-serve
More about this role
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,...
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