Senior AI/ML Engineer (Spectrum)

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. Spectrum aims to revolutionize the semantic layer space for software-building organizations by introducing a living spec extracted from the whole system to keep it aligned. Spectrum is the single source of truth for all product and architectural knowledge. It is a resident of JetBrains' startup incubator, combining startup speed and autonomy with 25 years of developer tooling expertise.

• At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
• 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.
• Experience with agentic frameworks such as LangGraph, Pydantic AI, or equivalents.
• Experience with retrieval-augmented generation (RAG) patterns and vector databases.
• Experience deploying and scaling LLM-powered applications using APIs (e.g., OpenAI or Anthropic) or open-source models.
• Strong Python skills; Kotlin knowledge is a plus.
• Excellent communication skills to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Nice to have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups and the zero-to-one phase.
• Background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Contributions to relevant open-source projects or publications.

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
• Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving AI agents, including prompt engineering, model selection, and inference optimization.
• Contributing to MLOps practices, including orchestration, observability, and experiment tracking.

We are an equal opportunity employer committed to creating an open and inclusive workplace welcoming everyone regardless of background, identity, religion, age, accessibility needs, or orientation.