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Senior Research Engineer (Code World Models)

8 hours, 5 minutes ago
Serbia, Spain, United Kingdom, Czech Republic, Germany, Netherlands, Poland, Cyprus, Armenia
Senior
Research Scientist
Software Development
Machine Learning NLP Python
Apply Now
JetBrains

JetBrains

JetBrains provides cutting-edge development tools like IntelliJ IDEA and Kotlin, automating tasks to boost productivity and foster innovation.

Internet Software & Services
1K-5K
Founded 2000
View All Jobs 48

Description

  • Design and run pre-training, continued pre-training, and mid-training experiments for code models.
  • Build and improve large-scale data pipelines for model training, including filtering, deduplication, mixture design, and dataset quality checks.
  • Work with code corpora, repositories, tests, execution traces, and synthetic data.
  • Develop evaluations for complex repository-level code reasoning tasks.
  • Collaborate with researchers and engineers working on machine learning for code and AI developer tools.

Requirements

  • Hands-on experience with model pre-training, continued training, or mid-training.
  • Strong engineering skills in Python and experience with modern machine learning frameworks.
  • Understanding of large-scale ML training workflows, including data processing, distributed training, checkpointing, evaluation, experiment tracking, and debugging.
  • Experience working with large datasets and attention to data quality, contamination, sampling, and reproducibility.
  • Background in NLP, ML for software engineering, or a similar domain.
  • Ability to work on high-uncertainty research problems and turn ideas into working experiments.
  • Experience training or adapting models for code generation, code understanding, software agents, program repair, test generation, or repository-level reasoning is a plus.
  • Experience with execution-based data such as unit tests, traces, logs, compiler feedback, runtime states, or sandboxed code execution is a plus.
  • Experience with large-scale distributed training of models with 70B+ parameters is a plus.
  • Understanding of evaluation challenges for code models, including benchmark contamination, flaky tests, execution-based scoring, and long-horizon task evaluation is a plus.
  • Contributions to ML infrastructure, open-source projects, or research systems is a plus.

Interested in this position?

Apply directly on the company website

Apply Now

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