Compute Intelligence Engineer
Prime Intellect builds the 'Open Superintelligence Stack' — an integrated compute, training, inference, and sandbox platform that lets companies train, deploy, and continuously improve their own AI models and agents. It serves AI startups, 'neolabs', and enterprises (over 6,000 customers, including Ramp and Zapier) that want to own their model optimization loop rather than rely solely on closed frontier labs.
Maintainer signals as of 8/12/2026
Funding history
Investors
Projects
About Prime Intellect
Prime Intellect is a San Francisco-based AI infrastructure company building what it calls the Open Superintelligence Stack: a full-stack platform spanning GPU compute (on-demand and reserved clusters), large-scale reinforcement learning training ('Lab'), an Environments Hub with 2,500+ community RL environments, hosted evaluations, sandboxed code execution, and dedicated/serverless model inference with native LoRA support. The company maintains open-source libraries (verifiers and prime-rl) used to build and train RL environments, and publishes frontier open research such as the INTELLECT and SYNTHETIC model/dataset series. Prime Intellect works with AI startups, enterprises, and 'neolab' customers such as Ramp and Zapier, helping them turn production traces and evaluations into custom-trained, post-trained agent models that outperform closed frontier models on specific workflows at lower cost and latency. The company has raised over $150M in total funding, including a $130M Series A led by Radical Ventures with participation from NVIDIA Ventures, Intel Capital, and Dell Technologies Capital, and reports over $100M in annualized revenue.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will build the data infrastructure and intelligence platform that provides a live view of compute supply, demand, utilization, capacity, and economics. You will establish the warehouse, develop production pipelines and data models, create dashboards and queryable data interfaces, and support cross-functional teams with reliable information.
Requirements
- 3–7+ years in data engineering, analytics engineering, GTM/growth engineering, or similar roles
- Data warehouse development and maintenance
- Production-quality Python and SQL pipelines
- Data modeling with dbt or equivalent
- API integrations
- Snowflake, BigQuery, or Databricks
- Airflow, Dagster, or equivalent orchestration tools
- BI and dashboarding tools
- Modern AI tooling
Responsibilities
- Stand up the data warehouse and pipelines
- Build data models and transformations
- Create dashboards and reporting
- Build an AI-accessible query layer
- Track compute supply, commitments, capacity, and utilization
- Connect supply data to demand signals
- Support Growth, Compute Partnerships, and Research with shared data
- Establish data quality, documentation, and infrastructure standards
- Build reliable unattended pipelines
Benefits
- Meaningful equity
- Flexible work with remote or San Francisco options
- Visa sponsorship
- Relocation support
- Professional development budget
- Team off-sites and conferences