Research Engineer – Data and Evaluation

Prime Intellect

. Design and build challenging evaluations for coding and long-horizon agents .

Posted 10/16/2026full-timeSan Francisco • California • United StatesMid-LevelSenior💰 $150,000 - $350,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates strong software engineering skills in Python, with a focus on building data pipelines and evaluation systems for machine learning workflows. Capable of investigating model failures and collaborating with researchers to enhance performance through rigorous experimentation and validation.

Highest-signal resume keywords

Python ProgrammingData Pipeline DevelopmentEvaluation MethodologyModel Failure AnalysisReproducible Research Tooling

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Hard Skills

Software EngineeringMachine Learning WorkflowsStatistical TestingSynthetic Data GenerationExperiment AnalysisDebuggingReward DesignTask ImplementationEvaluation SystemsAgent Environments

Soft Skills

CollaborationProblem-SolvingCommunication

Tools & Technologies

VerifiersPrime-RLDistributed ProcessingLong-Horizon Coding Agents

Industry Keywords

Reinforcement LearningModel-Based GradingDataset CurationContamination DetectionReward Exploitation

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Design and build challenging evaluations for coding and long-horizon agents
Build executable environments in Verifiers, with realistic task setup and clear success criteria
Develop and test scoring logic and verifiers, investigating reward hacks and misleading measures of progress
Trace failures through model outputs and harness code to distinguish model limitations from problems in the environment or scoring
Build and scale RL data pipelines that generate and curate challenging coding and agentic tasks
Work with RL researchers to test whether changes to tasks and training data improve performance on held-out tasks
Investigate model failures directly with researchers, from task implementation through success scoring

Requirements

What you’ll need

Strong software engineering skills in Python and experience building data pipelines, evaluation systems, or ML workflows used by others
Hands-on experience working with language models or agents, with an understanding of how training data and evaluation choices affect model behavior
Ability to inspect complex data and model outputs, identify failure modes, and turn an ambiguous quality question into a testable measurement
A record of owning technical projects through experimentation, implementation, and validation, while collaborating closely with researchers and engineers
Hands-on experience building technical evaluations or agent environments, with the engineering depth to inspect model traces and debug harness and scoring code
Experience with large-scale synthetic data generation, dataset curation, or distributed processing for model training
Experience with evaluation methodology, executable coding tasks, agent environments, verifiers, or reward design
Experience with experiment analysis, statistical testing, contamination detection, and reproducible research tooling
Nice to have: Experience with RL or post-training data, including task difficulty selection and analysis of rollout or reward distributions
Nice to have: Contributions to Verifiers, Prime-RL, or comparable environment and evaluation frameworks
Nice to have: Work on model-based grading, long-horizon coding agents, or diagnosing reward exploitation

Benefits

Comp & perks

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