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 in-house developed models for writing and coding assistance, as well as integration with our strategic partners.
We are looking for a Senior ML Engineer who can contribute to the development of our writing assistance tools. You will be involved in crafting and fine-tuning compact and efficient language models to help users write better text, no matter what JetBrains product they are using.
We value engineers who:
- Take their own initiative and make decisions independently, consulting with others if needed.
- Identify customer needs and prioritize their tasks accordingly.
- Implement the simplest possible solutions first, gradually adding complexity as needed.
- Can 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 NLP field.
In this role, you will:
- Work with stakeholders to convert business requirements into technical specifications.
- Develop and enhance the natural language platform for tasks such as grammatical error correction, text completion, paraphrasing, summarization, and more.
- Improve data processing, training, and inference pipelines.
- Come up with ways to evaluate ML features in both offline and online setups.
- Collaborate closely with applied linguists and data engineers.
We’ll be happy to have you on our team if you have:
- Proven experience in the design and deployment of ML systems.
- A solid theoretical understanding of NLP and transformer-based methods.
- Proficiency in modern deep learning frameworks such as PyTorch, along with commonly used libraries for NLP.
- An enthusiastic interest in working with natural languages.
- Practical Python language skills.
We’d be especially thrilled if you have experience with :
- LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
- MLOps tools and practices, including CI/CD for ML.
- K8s and Kubeflow.
- Kotlin and JVM.
How we develop JetBrains AI:
- Git as our version control system.
- Python, PyTorch, and Hugging Face as our ML stack.
- Kubeflow and Weights & Biases for experiment tracking and reports.
- TeamCity as our CI automation system.
- Cloud computing infrastructure on AWS and GCP.