📋 Descripción
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<p>JetBrains is a global software company that creates intelligent tools for software developers and teams. Since 2000, we have built products that help developers work more productively, write higher-quality code, and stay focused on solving real problems.</p>
<p>The JetBrains Research team is looking for a Senior Research Engineer to work on Code World Models: models that learn how software systems behave, change, execute, and interact with developer tools.</p>
<p>This role is focused on model pre-training and mid-training for code-centric foundation models. You will work on data, training pipelines, evaluation, and experiments that improve how models understand programs, repositories, execution, tests, and software engineering workflows.</p>
<h2>In this role, you will:</h2>
<ul>
<li>Design and run pre-training, continued pre-training, and mid-training experiments for code models.</li>
<li>Build and improve data pipelines for large-scale model training, including filtering, deduplication, mixture design, and dataset quality checks.</li>
<li>Work with code corpora, repositories, tests, execution traces, and synthetic data.</li>
<li>Develop evaluations for complex repository-level code reasoning tasks.</li>
<li>Collaborate with researchers and engineers working on ML for code and AI developer tools.</li>
</ul>
<h2>We’ll be happy to have you on our team if you:</h2>
<ul>
<li>Have hands-on experience with model pre-training, continued training, or mid-training.</li>
<li>Have strong engineering skills in Python and experience with modern ML frameworks.</li>
<li>Understand large-scale ML training workflows, including data processing, distributed training, checkpointing, evaluation, experiment tracking, and debugging.</li>
<li>Have experience working with large datasets and care about data quality, contamination, sampling, and reproducibility.</li>
<li>Have a background in NLP, ML for software engineering, or a similar domain.</li>
<li>Enjoy working on research problems with high uncertainty and turning ideas into working experiments.</li>
</ul>
<h2>It would be a plus if you:</h2>
<ul>
<li>Have experience training or adapting models for code generation, code understanding, software agents, program repair, test generation, or repository-level reasoning.</li>
<li>Have worked with execution-based data, such as unit tests, traces, logs, compiler feedback, runtime states, or sandboxed code execution.</li>
<li>Have experience with large-scale distributed training of models with 70B+ parameters.</li>
<li>Understand evaluation challenges for code models, including benchmark contamination, flaky tests, execution-based scoring, and long-horizon task evaluation.</li>
<li>Have contributed to ML infrastructure, open-source projects, or research systems.</li>
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</section><div class="content-conclusion"><p><strong>We are an equal opportunity employer</strong><br><br>We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.</p>
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