Train, deploy, and continuously improve your own models on an integrated compute, training, inference, and sandbox stack. Backed by Menlo.
About the role
Find, evaluate, and collect valuable training data from web, code, and technical sources. Build scalable pipelines that turn raw data into training-ready corpora through extraction, cleaning, deduplication, and filtering. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Strong programming skills in Python and a record of building reliable data-processing or distributed systems
- Experience working with large datasets and managing the practical tradeoffs of storage, compute, throughput, and reproducibility
- Ability to diagnose data-quality issues and translate research goals into measurable checks and experiments
- Comfort owning an evolving technical problem end to end and working closely with researchers to test assumptions and improve the system
- Web crawling, document extraction, code-data collection, or large-scale corpus curation
- Deduplication, text classification, quality scoring, synthetic data, or training-data contamination analysis
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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