Research Engineer (Agentic Models)

JetBrains·Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; London, United Kingdom; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia·16 янв.

Research Engineer (Agentic Models)

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Наша компания

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. 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.

О роли

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.

Чем предстоит заниматься

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

Наши требования

Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting

Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar)

Strong theoretical and practical understanding of LLM fundamentals: architectures, 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 developers actually use agents 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

Дополнительно

ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM

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

Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks

AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns

Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar

Inference optimization and serving optimized models in production

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

JetBrains

Amsterdam, Netherlands; Belgrade, Serbia; Berlin, Germany; Limassol, Cyprus; London, United Kingdom; Madrid, Spain; Munich, Germany; Paphos, Cyprus; Prague, Czech Republic; Remote, Germany; Warsaw, Poland; Yerevan, Armenia

ГрейдMiddle

ЗанятостьПолная занятость

РегионВеликобритания

ФорматУдалённо

ИсточникСкрыто

Опубликовано16 янв.

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