> Markdown version of [/jobs/ext/3568330-founding-ml-engineer-spectrum](https://www.wearedevelopers.com/jobs/ext/3568330-founding-ml-engineer-spectrum). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Founding ML Engineer (Spectrum)

- **Company:** JetBrains GmbH
- **Location:** Berlin, Germany
- **Experience:** Experienced
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Static Program Analysis, Programming Tools, Graph Database, Information Extraction, Python (Programming Language), Inference Optimization, OpenAI, Software Engineering, JetBrains, Data Ingestion, LangChain, Retrieval-Augmented Generation, Open-source Models, Large Language Models, Multi-Agent Systems, Prompt Engineering, Model Validation, Llamaindex, Agentic-AI, Kotlin, LangSmith, Smolagents, Machine Learning Operations
- **Published:** October 3, 2026
- **Apply:** https://www.arbeitsagentur.de/jobsuche/jobdetail/10001-1003340862-S

## About the Role

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.

## Description

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.