---
title: 'Research Engineer - Pretraining Data at Prime Intellect'
canonical: 'https://feeny.ai/job/research-engineer-pretraining-data-prime-intellect-san-francisco-fbgk1zsg5rfx'
type: 'job'
last_seen: '2026-10-19'
---

# Research Engineer - Pretraining Data at Prime Intellect

- **Company:** Prime Intellect
- **Location:** San Francisco, CA
- **Employment:** full-time
- **Posted:** 2026-10-16
- **Last confirmed live:** 2026-10-19
- **Apply:** https://jobs.ashbyhq.com/primeintellect/eecf9af5-46fb-4b62-b8c8-921098fd6514

## Job description

Own Your Intelligence 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.

## Role Impact

Build the data behind Prime Intellect’s next generation of open models. You’ll find valuable sources, turn them into training-ready corpora, and work with researchers to test what actually improves the model. Your work will shape both broad pretraining and the data used to develop reasoning, coding, and long-context capabilities.

## Responsibilities

- 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.
- Develop checks for data quality, coverage, and contamination, and use them to improve collection and processing.
- Work with researchers on data mixtures and sampling strategies for pretraining and midtraining.
- Prepare and evaluate data for long-context learning, reasoning, and coding, testing synthetic data where it proves useful.
- Run controlled data experiments and use model evaluations to decide which sources, mixtures, and processing choices are worth scaling.
- Make large-scale data processing efficient, reproducible, and recoverable, with clear source provenance and dataset versioning.

## Requirements

- 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.

Relevant experience may include:

- Web crawling, document extraction, code-data collection, or large-scale corpus curation.
- Deduplication, text classification, quality scoring, synthetic data, or training-data contamination analysis.
- Data-mixture experiments, curriculum learning, or measuring how dataset changes affect model performance.

## Nice to have

- Experience preparing datasets for language-model pretraining, continued pretraining, or midtraining.
- Work with distributed processing frameworks such as Spark, Ray, or comparable systems.
- Experience with multilingual, mathematical, scientific, or repository-level code data.
- Familiarity with tokenization, training data loaders, and the needs of large model-training runs.

Depth in data acquisition, scalable processing, or data research can be a strong starting point. We don’t expect every candidate to have worked across all of them.

## Benefits and Perks

- Cash Compensation Range of $150-350k, including equity incentives, aligning your success with the growth and impact of Prime Intellect.
- Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.
- Visa sponsorship and relocation assistance for international candidates.
- Quarterly team off-sites, hackathons, conferences and learning opportunities.
- Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.

If you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you.

## About Prime Intellect

## Company Overview
- **One-liner**: Prime Intellect provides an open, full-stack platform for companies to train, deploy, and continuously improve their own AI models through large-scale distributed reinforcement learning.
- **Entity Type**: Private (Series B)
- **Headquarters**: San Francisco, California, United States
- **Founded**: 2023
- **Founders**: Vincent Weisser (CEO), Johannes Hagemann (CTO)

## Core Business
- **Primary industry**: AI infrastructure, open-source AI research, and agentic training platforms
- **Target customers**: B2B — enterprises and AI labs that want to train custom models without building their own infrastructure; also open-source community contributors
- **Mission**: Democratize frontier AI training by making it accessible to every company and collectively owning the resulting open innovations.

## Products & Services
- **Compute**: Access to GPU clusters (H100, H200, B200+) from 50+ providers, plus on-demand single GPU instances and reserved clusters with InfiniBand networking and SLURM/K8s orchestration.
- **Hosted Training (Lab)**: Managed large-scale reinforcement learning (RL) training without infrastructure overhead, including a 2,500+ environment hub and custom eval benchmarks.
- **Inference**: Serverless or dedicated inference for custom models, with native LoRA support and 1-click deployment.
- **Open-Source Libraries**: `prime-rl` (async RL framework), `verifiers` (environments & evals), and environment hub for collaborative development.
- **INTELLECT-3**: A 100B+ parameter Mixture-of-Experts model trained on their RL stack, achieving state-of-the-art performance for its size.

## Market Standing
- **Valuation/Market Cap**: Not publicly disclosed
- **Total Funding**: $70.44M across multiple rounds (CBInsights, 2026); earlier reports indicated $20.5M in seed rounds, followed by a Series B round of $49.94M led by Founders Fund and other investors.
- **Notable Investors/Partners**: Founders Fund, CoinFund, Distributed Global, Radical Ventures, Andrej Karpathy, Clem Delangue (Hugging Face), Dylan Patel (SemiAnalysis), Tri Dao (Together AI).
- **Growth Signals**: Headcount grew 128.6% YoY to 36 employees; 24 active job postings (monthly job growth +26.3%); launched INTELLECT-3 and SYNTHETIC-2 datasets; customers include Ramp and Zap; operates in 9 countries.

## Competitive Advantages
- **Full-stack integrated platform** – compute, post-training, evals, and inference in one place, reducing the fragmentation of building and maintaining AI workflows.
- **Large-scale distributed RL expertise** – proven ability to train 100B+ models across clusters (global training via their RL stack).
- **Open-source ethos** – models, datasets, and libraries are released openly, attracting a community of researchers and developers.
- **Founding team & research edge** – strong ties to frontier AI research, with contributions like prime-rl and self-improving agent loops.

## Strategic Focus
- **Self-improving agents** – building infrastructure that closes the loop from deployment back to training, enabling models to compound performance over time.
- **Scaling RL at extreme sizes** – recent research (RL at 1T Scale) shows commitment to massive-scale reinforcement learning.
- **Enterprise adoption** – adding dedicated solutions engineers and managed workflows for corporate customers.

## Why Work Here
- **Culture**: Seeks “the most ambitious developers” and emphasizes cutting-edge research and engineering. The team includes former engineers from Together AI, Aleph Alpha, and Anyscale.
- **Remote/Hybrid**: Remote-friendly with HQ in San Francisco.
- **Growth trajectory**: Rapidly scaling company (headcount up 128% YoY) with multiple open roles across engineering, research, and go-to-market.
- **Tech stack**: Python, PyTorch, CUDA, Kubernetes, SLURM, Grafana, and a broad modern AI toolchain – opportunity to work on infrastructure-level challenges.

## Sources
1. [primeintellect.ai](https://www.primeintellect.ai/)
2. [linkedin.com/company/primeintellect-ai](https://www.linkedin.com/company/primeintellect-ai)
3. [jobs.ashbyhq.com/PrimeIntellect](https://jobs.ashbyhq.com/primeintellect)
4. [cbinsights.com/company/prime-intellect](https://www.cbinsights.com/company/prime-intellect)
5. [docs.primeintellect.ai/introduction](https://docs.primeintellect.ai/introduction)

## Other roles at Prime Intellect

- [Research Engineer - RL Infrastructure](https://feeny.ai/job/research-engineer-rl-infrastructure-prime-intellect-san-francisco-faaejgnzefb8) — San Francisco, CA
- [Research Engineer - Data and Evaluation](https://feeny.ai/job/research-engineer-data-and-evaluation-prime-intellect-san-francisco-pbeyv35k8888) — San Francisco, CA
- [Research Engineer - Pretraining](https://feeny.ai/job/research-engineer-pretraining-prime-intellect-san-francisco-zemr10qw9rtd) — San Francisco, CA
- [Research Engineer - Inference](https://feeny.ai/job/research-engineer-inference-prime-intellect-san-francisco-1rywfz5aktgb) — San Francisco, CA
- [Research Engineer / Scientist - Reinforcement Learning](https://feeny.ai/job/research-engineer-scientist-reinforcement-learning-prime-intellect-san-francisco-14pw1t4w47jd) — San Francisco, CA
- [Member of Technical Staff - Datacenter Networking](https://feeny.ai/job/member-of-technical-staff-datacenter-networking-prime-intellect-san-francisco-nad0z4zmmdmc) — San Francisco, CA
- [Member of Technical Staff - Storage Infrastructure](https://feeny.ai/job/member-of-technical-staff-storage-infrastructure-prime-intellect-san-francisco-039n2ahf9xzy) — San Francisco, CA
- [Product Marketing Lead](https://feeny.ai/job/product-marketing-lead-prime-intellect-san-francisco-qmet74zfdsaq) — San Francisco, CA
- [Strategic Account Executive - AI Infrastructure](https://feeny.ai/job/strategic-account-executive-ai-infrastructure-prime-intellect-san-francisco-hv0skjf5w6zy) — San Francisco, CA
- [Founding Solutions Architect](https://feeny.ai/job/founding-solutions-architect-prime-intellect-san-francisco-rrwa9hfn3xgq) — San Francisco, CA