Train, deploy, and continuously improve your own models on an integrated compute, training, inference, and sandbox stack. Backed by Menlo.
About the role
Design and build challenging evaluations for coding and long-horizon agents. Build executable environments in Verifiers, with realistic task setup and clear success criteria. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong software engineering skills in Python and experience building data pipelines, evaluation systems, or ML workflows used by others
- Hands-on experience working with language models or agents, with an understanding of how training data and evaluation choices affect model behavior
- Ability to inspect complex data and model outputs, identify failure modes, and turn an ambiguous quality question into a testable measurement
- A record of owning technical projects through experimentation, implementation, and validation, while collaborating closely with researchers and engineers
- Hands-on experience building technical evaluations or agent environments, with the engineering depth to inspect model traces and debug harness and scoring code
- Large-scale synthetic data generation, dataset curation, or distributed processing for model training
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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