Research Engineer – Agentic Models
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Job Description
Research Engineer responsible for AI-powered coding agents at JetBrains. Focusing on multi-step workflows and large-scale infrastructure for training and evaluation.
Responsibilities:
- Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
- Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
- Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
- Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
- Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
- Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
- Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features.
Requirements:
- Hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
- Experience with a modern deep learning framework, such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
- A solid understanding of LLM training basics – tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
- The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
- A product-aware mindset – you care about how agents are actually used by developers and can translate product needs and failure modes into modeling and evaluation work.
- At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.
Benefits:
- Health insurance
- Employee development opportunities
- Flexible working hours
- Team building events
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