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About the Role
Prime Intellect is building the open superintelligence stack, providing infrastructure for ambitious AI teams. Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment for post-training at frontier scale. We are developing open frontier AI, including open-source models for long-horizon tasks and the platform to build them. We seek individuals passionate about building at the intersection of frontier research, real infrastructure, and go-to-market strategy in a nascent category.
Responsibilities
- Build and extend pretraining code, scaling experiments to full training runs.
- Evaluate model architecture changes for quality and training cost.
- Profile training jobs and improve end-to-end throughput.
- Ensure long run resilience with reliable checkpointing and recovery.
- Investigate training dynamics and numerical stability.
- Run controlled ablations for reproducible results.
- Collaborate on training mixtures and midtraining/long-context experiments.
Requirements
- Hands-on experience training language models, including modifying training code.
- Strong Python skills and experience with PyTorch or a comparable framework.
- Sufficient systems understanding to debug distributed training.
- Practical understanding of model architectures and optimization.
- Ability to design and interpret ablation studies.
- Good judgment for prioritizing investigations and seeking collaboration.
Skills
- Python
- PyTorch
- Distributed Training
- Model Architectures
- Optimization
- Ablation Studies
Location
- San Francisco
- Remote
Work Type
- Remote
- In-person
Experience Level
- Mid-level
- Senior
Salary/Compensations
- $150,000 - $350,000
Benefits
- Cash compensation including equity incentives
- Flexible work arrangements
- Visa sponsorship and relocation assistance
- Quarterly team off-sites, hackathons, conferences, and learning opportunities
About the Company
- 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.