Research Engineer - Pre-training Data

The role

You will build the data behind Prime Intellect's next generation of open models. This involves finding and collecting training data, building scalable processing pipelines, and working with researchers to test data mixtures and sampling strategies.

What you will do

• 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 pre-training 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.

Required qualifications

• 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.

Nice to have

• 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.
• Experience preparing datasets for language-model pre-training, continued pre-training, 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.

Benefits

• Cash Compensation Range of $150-350k, including equity incentives
• 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

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.