<div class="show-more-less-html__markup show-more-less-html__markup--clamp-after-5 relative overflow-hidden"> At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.<br/><br/>We’re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you’ll be responsible for the models, training loops, and evaluation pipelines that power these agents.<br/><br/>You’ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.<br/><br/><strong>As Part Of Our Team, You Will<br/><br/></strong><ul><li>Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.</li><li>Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.</li><li>Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.</li><li>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.</li><li>Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.</li><li>Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.</li><li>Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features. <br/><br/></li></ul>We’ll be happy to bring you on board if you have:<br/><br/><ul><li>Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.</li><li>Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).</li><li>Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.</li><li>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.</li><li>A product-aware mindset – you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.</li><li>At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.<br/><br/></li></ul><strong>Our Ideal Candidate Would Have Experience With<br/><br/></strong><ul><li>ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.</li><li>Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.</li><li>Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.</li><li>AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.</li><li>Experiment tracking and observability using tools like Weights &amp; Biases, MLflow, Langfuse, or similar.</li><li>Inference optimization and serving optimized models in production.<br/><br/></li></ul><strong>We are an equal opportunity employer<br/><br/></strong>We know great ideas can come from anyone, anywhere. That’s why we do our best to create an open and inclusive workplace – one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.<br/><br/><em>We process the data provided in your job application in accordance with the Recruitment Privacy Policy.<br/><br/></em> </div>