ml engineer for developer tools

Spectrum collects data from an organization's code, documentation, and issues and organizes it into a unified ontology that AI agents can search and reason over. The product provides a living specification and a single source of truth for product and architectural knowledge.

• Design and build ML/LLM solutions for data ingestion, knowledge extraction, retrieval, and reasoning;
• Create datasets, metrics, and pipelines that drive measurable system improvements;
• Architect and improve agents for context retrieval, knowledge extraction, and data alignment, including prompt engineering, model selection, and inference optimization;
• Establish MLOps practices, including orchestration, observability, and experiment tracking;
• Collaborate with the engineering team on system design and with JetBrains Research on the research agenda;
• Define hiring criteria, grow the ML team, and shape the ML team culture.

• Proven track record as an ML/AI Lead;
• At least five years of experience in ML/AI systems, including at least two years focused on LLMs and generative AI;
• 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;
• Hands-on experience with agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent;
• Experience with vector databases and retrieval-augmented generation (RAG) patterns;
• Experience deploying and scaling LLM-powered applications using APIs such as OpenAI or Anthropic, or open-source models;
• Strong Python skills;
• Excellent communication skills and the ability to explain complex technical concepts to diverse audiences;
• Proficiency in English, both written and verbal;
• Nice to have: Kotlin knowledge, experience with ontologies, knowledge graphs or graph-based reasoning, early-stage startup experience, strategic thinking about product-led AI, a background in code analysis, developer tools or software engineering research, multi-agent systems or complex agentic workflows, contributions to relevant open-source projects or publications.

• Competitive salary and JetBrains benefits;
• Generous runway and corporate resources with startup autonomy.