Qureos Mentor

JetBrains

JetBrains is on a mission to enhance software development, making it more productive and enjoyable. The company specializes in creating developer tools, integrated development environments (IDEs), and productivity software, catering to a wide range of programming needs. Founded in 2000 and headquartered in Amsterdam, JetBrains offers various products, including IntelliJ IDEA, PyCharm, and TeamCity, aimed at improving code quality and project management for developers.

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

<div>
 At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.
 
 
 We&rsquo;re looking for a Research Engineer who will own the training stack and model architecture for our Mellum LLM family. Your job is easier said than done: make training faster, cheaper, and more stable at a large scale. You&rsquo;ll profile, design, and implement changes to the training pipeline &ndash; from architecture to custom GPU kernels, as needed.
 
 
 
 As Part Of Our Team, You Will
 
 
 
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 Be responsible for improving end-to-end performance for multi-node LLM pre-training and post-training pipelines.
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 Profile hotspots (Nsight Systems/Compute, NVTX) and fix them using compute/comm overlap, kernel fusion, scheduling, etc.
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 Design and evaluate architecture choices (depth/width, attention variants including GQA/MQA/MLA/Flash-style, RoPE scaling/NTK, and MoE routing and load-balancing).
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 Implement custom ops (Triton and/or CUDA C++), integrate via PyTorch extensions, and upstream when possible.
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 Push memory/perf levers: FSDP/ZeRO, activation checkpointing, FP8/TE, tensor/pipeline/sequence/expert parallelism, NCCL tuning.
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 Harden large runs by building elastic and fault-tolerant training setups, ensuring robust checkpointing, strengthening reproducibility, and improving resilience to preemption.
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 Keep the data path fast using streaming and sharded data loaders and tokenizer pipelines, as well as improve overall throughput and cache efficiency.
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 Define the right metrics, build dashboards, and deliver steady improvements.
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 Run both pre-training and post-training (including SFT, RLHF, and GRPO-style methods) efficiently across sizable clusters.
 
 
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 We&rsquo;ll be happy to bring you on board if you have:
 
 
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 Strong PyTorch and PyTorch Distributed experience, having run multi-node jobs with tens to hundreds of GPUs.
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 Hands-on experience with Megatron-LM/Megatron-Core/NeMo, DeepSpeed, or serious FSDP/ZeRO expertise.
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 Real profiling expertise (Nsight Systems/Compute, nvprof) and experience with NVTX-instrumented workflows.
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 GPU programming skills with Triton and/or CUDA, and the ability to write, test, and debug kernels.
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 A solid understanding of NCCL collectives, as well as topology and fabric effects (IB/RoCE), and how they show up in traces.
 
 
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 Our Ideal Candidate Would Have Experience With
 
 
 
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 FlashAttention-2 and 3, CUTLASS and CuTe, TransformerEngine and FP8, Inductor, AOTAutograd, and torch.compile.
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 MoE at scale (expert parallel, router losses, capacity management) and long-context tricks (ALiBi/YaRN/NTK scaling).
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 Kubernetes or SLURM at scale, placement and affinity tuning, as well as AWS, GCP, and Azure GPU fleets.
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 Web-scale data plumbing (streaming datasets, Parquet and TFRecord, tokenizer perf), eval harnesses, and benchmarking.
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 Safety and post-training methods, such as DPO, ORPO, GRPO, and reward models.
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 Inference ecosystems such as vLLM and paged KV.
 
 
 </li>
 </ul>
 
 We are an equal opportunity employer
 
 
 
 We know great ideas can come from anyone, anywhere. That&rsquo;s why we do our best to create an open and inclusive workplace &ndash; one that welcomes everyone regardless of their background, identity, religion, age, accessibility needs, or orientation.
 
 
 
 We process the data provided in your job application in accordance with the Recruitment Privacy Policy.
 
 
 
</div>

Research Engineer (LLM Training and Performance)

Join JetBrains and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

JetBrains

About Company

Research Engineer (Agentic Models)

Research Engineer (LLM Training and Performance)