At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
We are working on an ambitious new platform that provides AI capabilities to all JetBrains products. Our platform is based on models developed in-house for writing and coding assistance, as well as integration with our strategic partners.
We are looking for a Research Engineer who can contribute to training foundation models for coding tasks. You’ll be working on developing Large Language Models from scratch and deploying them into production environments where they will be accessible by end users across the globe.
We value engineers who:- Can plan projects and make decisions independently, consulting with others if needed.
- Identify customer needs and prioritize their tasks accordingly.
- Start with the simplest solutions and gradually add complexity as needed.
- Take sole responsibility for an entire subsystem.
- Have a passion for learning and a desire to stay up to date with the latest developments in the LLM field.
- Work with stakeholders to convert business requirements into technical specifications.
- Train LLMs from scratch on a large GPU cluster.
- Collect and process pre-training and fine-tuning datasets.
- Support and improve existing subsystems.
- Experience in design, deployment, and support of production ML systems.
- A strong theoretical background in NLP and transformer-based approaches.
- Proficiency with modern deep learning frameworks such as PyTorch and common libraries for NLP.
- Experience in distributed training of multi-billion parameter models.
- Attention to detail in everything you do and great communication skills.
- LLM inference frameworks such as vLLM, DeepSpeed, TensorRT.
- LLM alignment techniques such as RLHF/RLAIF.
- MLOps tools and practices, including CI/CD for ML.
- K8s and Kubeflow.
- Scientific publications in the NLP field.
- A cluster of hundreds of NVIDIA GPUs as training infrastructure.
- Git for source control management.
- Python, PyTorch, and HuggingFace as an ML stack.
- Kubeflow and Weights & Biases for experiment tracking.
- TeamCity as a CI Automation system.
#LI-KP1
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Skills Required
- Experience in design, deployment, and support of production ML systems
- Strong theoretical background in NLP and transformer-based approaches
- Proficiency with Python and deep learning frameworks such as PyTorch
- Experience with HuggingFace and common NLP libraries
- Experience in distributed training of multi-billion parameter models on large GPU clusters (NVIDIA GPUs)
- Ability to train LLMs from scratch and collect/process pretraining and fine-tuning datasets
- Attention to detail and strong communication skills
- Experience with LLM inference frameworks such as vLLM, DeepSpeed, TensorRT
- Experience with LLM alignment techniques such as RLHF or RLAIF
- Familiarity with MLOps tools and CI/CD for ML, including Kubeflow and Kubernetes
- Experience with experiment tracking tools like Weights & Biases and CI automation like TeamCity
- Scientific publications in the NLP field
JetBrains Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about JetBrains and has not been reviewed or approved by JetBrains.
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Fair & Transparent Compensation — Fair & Transparent Compensation: Pay is considered market-competitive for many product and engineering roles in key locations, with published salary ranges on some postings aiding expectation-setting. Feedback suggests total compensation feels fair relative to local markets even if packages are positioned as “competitive but not top‑of‑big‑tech”.
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Flexible Benefits — Flexible Benefits: Work setup includes hybrid/remote options and flexible hours across many locations. The ability to work abroad for part of the year adds practical flexibility to where work gets done.
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Leave & Time Off Breadth — Leave & Time Off Breadth: Time off includes additional vacation days beyond local minimums in many countries. U.S. materials also highlight PTO, sick leave, and holidays, underscoring breadth beyond statutory baselines.
JetBrains Insights
What We Do
JetBrains creates intelligent software development tools consistently used and trusted by 11.4 million professionals and 88 Fortune Global Top 100 companies. Our lineup of more than 30 products includes IDEs for most programming languages and technologies, such as IntelliJ IDEA, PyCharm, and others, as well as products for team collaboration, like YouTrack and TeamCity. JetBrains is also known for creating the Kotlin programming language, a cross-platform language used by more than 5 million developers worldwide yearly and recommended by Google as the preferred language for Android development. The company is headquartered in Prague, Czech Republic, and has offices around the world. JetBrains IDEs * IntelliJ IDEA (Java and Kotlin Developers) * PyCharm (Python developers) * PhpStorm (PHP developers) * GoLand (Go developers) * Rider (.NET developers) * CLion (C and C++ developers) * Rust Rover (Rust developers) * WebStorm (JavaScript & TypesScript developers) * RubyMine (Ruby and Rails developers) * DataGrip (Tool for multiple databases) * ReSharper (Extension for Visual Studio) * Fleet (Multilingual IDE and code editor) * Aqua (IDE for test automation engineers) .NET & Visual Studio: * Rider (IDE for .NET developers) * ReSharper (Extension for Visual Studio) * ReSharper C++ (Visual Studio Extension for C++ developers) * dotCover (.NET Unit Test Runner and Code Coverage Tool) * dotMemory (.NET Memory Profiler) * dotTrace (.NET Performance Profiler) * dotPeek (.NET decompiler and assembly browser) Team Tools: * TeamCity (Powerful CI out of the box) * YouTrack (Project management for all your teams) * Space (Intelligent code collaboration platform) * Datalore (Collaborative data science platform) * Qodana (Code quality platform for teams) Programming Languages: * Kotlin (Programming Language for the JVM and Android) * MPS (Create Your Own Domain-Specific Language) Education: * JetBrains Academy (Learn and Teach Computer Science) Profile by JetBrains s.r.o.
