Senior Research Engineer, Code World Models & ML for Code

Jetbrains; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

JetBrains is seeking a Senior Research Engineer to work on Code World Models, focusing on pre-training and mid-training for code-centric foundation models. You will develop data pipelines, run experiments, and help improve how models understand programs and software engineering workflows.

You will collaborate with researchers and engineers, work with Python and modern ML frameworks, and tackle large-scale datasets, contamination, and reproducibility.

Qualifications

• Hands-on experience with model pre-training, continued pre-training, or mid-training.
• Strong engineering skills in Python and experience with modern ML frameworks.
• Understand large-scale ML training workflows, including data processing, distributed training, checkpointing, evaluation, experiment tracking, and debugging.

Responsibilities

• Design and run pre-training, continued pre-training, and mid-training experiments for code models.
• Build and improve data pipelines for large-scale 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 ML for code and AI developer tools.

Skills

Pre-training

Continued training

Mid-training

Python

ML frameworks

Data pipelines

NLP

Code understanding

Experiment tracking

Reproducibility

Tools

Python

PyTorch

TensorFlow

Hugging Face Transformers

MLflow

Job description

JetBrains is seeking a Senior Research Engineer to work on Code World Models, focusing on pre-training and mid-training for code-centric foundation models. You will develop data pipelines, run experiments, and help improve how models understand programs and software engineering workflows.

You will collaborate with researchers and engineers, work with Python and modern ML frameworks, and tackle large-scale datasets, contamination, and reproducibility.