Senior Machine Learning Engineer

Munich Germany Ref: 2021

Senior Machine Learning Engineer

ABOUT THE COMPANY
Our client is building a no-code, agent-oriented AI platform designed for organisations that rely heavily on technical documentation, operational records, and complex knowledge workflows. Their platform specialises in automating high-value decision processes historically locked inside disparate document stores, legacy systems, and deep tacit expertise. Their multi-agent architecture enables sophisticated reasoning over large, evolving bodies of unstructured information, turning manual, consulting-driven processes into scalable, intelligent, software-powered operations. They collaborate with major enterprises across Europe, North America, LATAM, and Asia.

ROLE OVERVIEW
You will lead the development of the document-centric reasoning engine that powers our client’s agentic AI platform. Your work sits at the intersection of NLP, retrieval-augmented generation, knowledge-graph construction, and multi-agent inference. You will design and implement pipelines that convert raw document collections into structured, queryable, and semantically rich knowledge assets, with a focus on robust grounding, factual consistency, and domain-aware retrieval rather than generic LLM generation.

KEY RESPONSIBILITIES

• Build advanced NLP pipelines for extracting entities, relationships, constraints, and procedural details from large, heterogeneous document sets including PDFs, CAD specs, procedural manuals, contracts, and reports
• Architect scalable RAG workflows using hybrid search, document chunking strategies, embedding optimisation, and grounded generation approaches tailored to enterprise knowledge
• Automate the transformation of document-level insights into structured knowledge graphs, capturing dependencies, hierarchies, workflows, and cross-document relationships
• Develop agent-based inference pipelines that allow AI agents to perform multi-step reasoning, validation, and decision-making using retrieved evidence
• Implement systems that identify actionable opportunities, risks, requirements, or constraints embedded within textual content
• Bring state-of-the-art NLP and retrieval research into reliable production workflows that deliver measurable efficiency and quality gains for customers

PERSON SPECIFICATION

Essential

• MS or PhD in Computer Science, NLP, Information Retrieval, or a related field
• 3+ years of industry experience in large-scale NLP or information retrieval systems
• 2+ years leading projects in RAG, document intelligence, or knowledge-graph-based reasoning
• Experience with vector databases, hybrid retrieval, embedding optimisation, and LLM orchestration frameworks
• Expertise in libraries such as spaCy, HuggingFace Transformers, Haystack, LangChain, or similar
• Strong understanding of scalable, production-grade software systems
• Excellent English communication skills

Desirable

• Familiarity with agentic systems such as GraphRAG, LangGraph, or LlamaIndex
• Prior experience in a high-growth, fast-moving tech environment

Candidate Profile

• High ownership and autonomy — comfortable leading technical direction
• Collaborative, working well within an international team of NLP, knowledge-engineering, and software experts
• Motivated by pushing the boundaries of enterprise-grade AI systems
• Driven by long-term impact and meaningful technical challenges

HOW TO APPLY To apply, please send your CV and a covering letter to Arran Goodridge via [email protected] quoting the role title in the subject line.

Salary: Competitive