Founding ML Engineer: Architect AI-Driven Knowledge

JetBrains; Amsterdam; On-site; EUR 120,000 - 180,000; Full time

Benefits offered by this job

JetBrains benefits

Startup autonomy

Job summary

Spectrum, hosted by JetBrains, seeks an ML Engineer to own the AI/ML stack, shape research agendas, and drive data-driven product decisions. You will design and scale LLM-powered systems, from data ingestion to reasoning, collaborating with JetBrains Research and the broader engineering team.

Ideal candidates bring 5+ years in ML/AI systems, 2+ years with LLMs, and hands-on expertise in prompt engineering, vector databases, and multi-agent workflows.

Qualifications

• 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.
• Hands-on: Prompt engineering, LLM pipelines, evaluation.

Responsibilities

• 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, including 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.

Skills

Python

English communication

LLM concepts

Prompt engineering

System design

Tools

LangChain

LlamaIndex

LangSmith

smolagents

OpenAI API

Anthropic API

Kotlin

Job description

Spectrum, hosted by JetBrains, seeks an ML Engineer to own the AI/ML stack, shape research agendas, and drive data-driven product decisions. You will design and scale LLM-powered systems, from data ingestion to reasoning, collaborating with JetBrains Research and the broader engineering team.

Ideal candidates bring 5+ years in ML/AI systems, 2+ years with LLMs, and hands-on expertise in prompt engineering, vector databases, and multi-agent workflows.