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Founding ML Engineer (Spectrum)

jetbrains · Berlin; Munich; RemoteRemotesenior

In short

  • ▸Ingeniero ML fundador que construye y dirige el sistema de IA para organizar conocimiento técnico en código, documentación y issues.
  • ▸Día a día: diseño de pipelines de LLM, RAG, agentes inteligentes, métricas y MLOps para mejorar la extracción y razonamiento de conocimiento.
  • ▸Destacado: eres el primer ingeniero ML en un equipo que está creando una "especificación viva" para organizaciones de desarrollo de software.

Proficiency in English, both written and verbal.

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What they ask for

  • ✓Al menos 5 años de experiencia en sistemas de ML/AI, con 2 en LLMs y generative AI.
  • ✓Experiencia comprobada en ingeniería de LLMs: prompt engineering, fine-tuning, evaluación.
  • ✓Conocimiento práctico de frameworks agenticos como LangChain, LlamaIndex o equivalentes.
  • ✓Experiencia con bases de datos vectoriales y patrones RAG.
  • ✓Habilidades sólidas en Python; conocimiento de Kotlin es un plus.
  • ✓Capacidad para comunicar ideas técnicas complejas a distintos públicos.

Don't tick every box? That's normal — your free dossier shows your gaps and how to cover them in the interview.

PythonLLMsLangChainLlamaIndexLangSmithsmolagentsvector databasesRAGOpenAIAnthropic

Who should you write to at jetbrains?

Your free dossier identifies the people who'd interview you — their background, what they value, and how to reach out so you stand out before applying.

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge. Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success. Your responsibilities will include: • 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. We expect you to have: • 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. Our ideal candidate would have: • Experience with ontologies, knowledge graphs, or graph-based reasoning. • Experience in early-stage startups – you enjoy the zero-to-one phase. • The ability to think strategically about product-led AI, beyond just training models in isolation. • A background in code analysis, developer tools, or software engineering research. • Experience with multi-agent systems or complex agentic workflows. • Actively contributed to relevant open-source projects or publications. What we offer • A competitive salary and JetBrains benefits. • A generous runway and corporate resources with startup autonomy. #LI-KP1 <div class="content-conc

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