Senior AI/ML Engineer
Core
Building scalable memory, retrieval, and reasoning systems for an AI platform that helps organizations analyze complex information and make strategic decisions.
Role type
Senior AI Systems Engineer (Applied AI / Search & Retrieval)
Builds
Production-grade AI systems combining vector search, knowledge graphs, and agent orchestration for enterprise decision-making.
Domain
Artificial Intelligence, Search & Retrieval, Knowledge Graphs, Enterprise Decision Intelligence
Deliverable
production ML models | product features | infrastructure
Required skills
Python, LLM-based systems, retrieval pipelines, embeddings, agent orchestration, evaluation frameworks, Knowledge Graphs, API development, distributed systems observability, AI-native development tools
Preferred skills
Model fine-tuning and distillation, agentic systems, long-term memory architectures, sovereignty-driven model strategies, hybrid retrieval techniques, enterprise AI product deployment
Technologies
Neo4j, vector search, lexical search, structured data, Claude Code, Codex, Cursor, Gemini
Responsibilities
Build scalable memory and retrieval systems for high-context AI workflows; Design hybrid retrieval architectures combining vector search, knowledge graphs, and lexical search; Develop evaluation frameworks to benchmark retrieval quality and reasoning effectiveness; Build agent memory interfaces for context querying and reuse; Implement routing mechanisms for retrieval, reasoning, and agent-based workflows; Develop fine-tuning, distillation, and model adaptation pipelines; Build observability and monitoring solutions for AI workflows.
Seniority
Senior, hands-on IC
