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
Posted about 2 months ago
or apply directly on JetBrains's site. We never take the application ourselves.
Is this posting real?
- This role has been open
- 65 days JetBrains's roles stay open a median of 66 days
- Reposted
- No
- Salary listed
- No 0% of JetBrains's roles list one
- Ghost-job risk at JetBrains
- high 69 stale, 2 reposted of 73 open
- Hiring momentum
- 114 roles opened in the last 90 days ↑ up vs. the prior 90 days
- Last confirmed on the employer's board
- 2026-10-08
Measured from postings appearing on and disappearing from JetBrains's own greenhouse board since 2026-08-03. Full hiring picture for JetBrains.
About this role
As a Research Engineer in the Agentic Models team at JetBrains, you will focus on developing multi-step coding agents that assist developers within IDEs. Your responsibilities will include designing and maintaining training pipelines, training large language models (LLMs), and creating evaluation environments to assess agent performance. You will collaborate with various teams to translate product visions into actionable models and experiments, utilizing large-scale infrastructure for training and evaluation.
- benefits
- 1/5
- freshness
- 1/5
- career value
- 5/5
- role clarity
- 5/5
- pay transparency
- 0/5
Scored from the posting itself — how clearly the role is described, how much it says about pay and benefits, and how recently it was listed. Not a judgement of JetBrains as an employer.
What you need
- 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.
Nice to have
- 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.
Worth weighing
- No salary listed.
- Role involves working with large-scale infrastructure and distributed systems, which may require advanced technical skills.
- Focus on both research and practical application, which could appeal to candidates looking for a balance of theory and implementation.
Summarised from JetBrains's posting. Read the full original.
Listed by JetBrains on their greenhouse job board, last confirmed open on 2026-10-08. PitchMeAI is not the employer.
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