JetBrains

Founding ML Engineer – Spectrum

JetBrains

full-time

Posted on:

Location Type: Remote

Location: Netherlands

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Tech Stack

About the role

  • Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
  • Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
  • Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
  • Establishing MLOps practices, including orchestration, observability, and experiment tracking.
  • Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
  • Defining hiring criteria, growing the ML team, and shaping the ML team culture.

Requirements

  • A proven track record as an ML/AI Lead.
  • At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
  • A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
  • Hands-on experience with:
  • Prompt engineering and LLM pipeline design, including evaluation.
  • Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
  • Vector databases and retrieval-augmented generation (RAG) patterns.
  • Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
  • Strong Python skills – Kotlin knowledge would be a plus.
  • Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
  • Proficiency in English, both written and verbal.
Benefits
  • A competitive salary and JetBrains benefits.
  • A generous runway and corporate resources with startup autonomy.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
machine learningartificial intelligencelarge language modelsprompt engineeringmodel architecturesfine-tuningMLOpsPythonKotlinevaluation
Soft Skills
communicationteam leadershipcollaborationculture shapingexplanation of technical concepts