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Research Engineer (Agentic Models)

1 day, 20 hours ago
United Kingdom, Czech Republic, Germany, Netherlands, Poland, Serbia, Spain, Cyprus, Armenia
Senior
Research Scientist
Software Development
Apache Airflow Dagster Kubeflow Kubernetes LLM MapReduce MLflow Python PyTorch
Apply Now
JetBrains

JetBrains

JetBrains provides cutting-edge development tools like IntelliJ IDEA and Kotlin, automating tasks to boost productivity and foster innovation.

Internet Software & Services
1K-5K
Founded 2000
View All Jobs 73

Description

  • 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 evaluation and simulation environments where coding agents can perform and be measured on realistic developer tasks.
  • Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and feed results back into training, data, and reward design.
  • Analyze training and evaluation results to improve model architectures, training recipes, and datasets.
  • Work with large-scale infrastructure for distributed GPU training and MapReduce-style data processing for pre-training and fine-tuning datasets.
  • Collaborate with research, product, and infrastructure teams to turn product visions into models, experiments, and shipped features.

Requirements

  • Extensive hands-on experience training LLMs in pre-training, fine-tuning, or post-training settings in research or production.
  • Deep expertise in PyTorch and specialized LLM training stacks such as Megatron, NeMo, verl, or similar.
  • Strong understanding of LLM fundamentals, including architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
  • Ability to own projects end to end from problem definition through design, experimentation, implementation, and iteration.
  • Product-aware mindset with the ability to 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.
  • Experience with ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, Kubernetes, or SLURM.
  • Experience with large-scale data and training pipelines, including MapReduce-style clusters, multi-node GPU training, or 1M+ CPU/GPU hour workloads.
  • Experience designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
  • Experience with AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
  • Experience with tools such as Weights & Biases, MLflow, Langfuse, or similar for experiment tracking and observability.
  • Experience with inference optimization and serving optimized models in production.

Interested in this position?

Apply directly on the company website

Apply Now

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