Machine Learning Engineer; m​/f​/d

About Octonomy

At octonomy, we’re not a typical AI startup. We’re building big — backed by one of Europe’s largest seed rounds (€20M) to scale our vision fast and sustainably. Our mission is clear: we transform companies with the most intelligent digital workforce, enabling a new era of growth.

Our AI octo-Workers automate business processes with high reliability, strong security, and zero hallucinations. Leading customers already trust us — and we’re growing rapidly across Germany and internationally.

As Machine Learning Engineer (m/f/d), you will design and ship production‑grade AI systems at the intersection of machine learning, large language models, and agentic workflows. This is not a research‑only role — and not a generic model training role. You will take ownership of real AI systems that power automation in mission‑critical business environments.

• Build end-to-end AI systems in production: develop, deploy, and operate ML and LLM‑based models that deliver measurable impact.
• Work on modern LLM architectures: design and improve systems such as RAG pipelines, tool‑using agents, and multi‑step reasoning workflows.
• Own reliability and evaluation: set up robust evaluation frameworks, monitoring, and guardrails to ensure consistent performance and minimal hallucinations.
• Develop scalable ML infrastructure: improve training workflows, deployment pipelines, and automation (CI/CD for ML, reproducibility, model lifecycle).
• Shape knowledge‑centric AI solutions (future direction): contribute to building structured knowledge bases, potentially involving ontology‑driven knowledge graphs.
• Lead technical projects end-to-end: drive architecture decisions, establish best practices, and mentor others as we scale our AI engineering organization.

• Strong experience shipping ML systems: several years of experience building and deploying models in real‑world production environments.
• LLM & agentic systems expertise: hands‑on work with large language models, RAG setups, orchestration frameworks, or agentic workflows.
• Research mindset and culture: experience from R&D, publications, or advanced academic work is a plus — but most importantly, you work systematically: experimentation, documentation, and best practices.
• Solid software engineering fundamentals: proficiency in Python and ML frameworks, with clean, tested, maintainable code.
• ML Ops and production ownership: comfortable with Docker, CI/CD, monitoring, and operating models beyond initial training.
• Leadership and project ownership: proven ability to lead complex technical projects end-to-end (Staff/Principal mindset is a strong plus).

• A role with real ownership: you’ll directly improve the day‑to‑day experience of the team.
• A fast‑moving environment where quality and pragmatism matter.
• Close collaboration with experienced IT Operations and a global team.
• Flexible working hours that fit around your studies.
• The opportunity to grow into broader IT Ops topics (tooling, processes, security basics).

octonomy ist ein KI-Unternehmen mit Sitz in Köln, das sich auf die Entwicklung intelligenter KI-Agenten zur Automatisierung von Unternehmensprozessen spezialisiert hat. Mit seiner innovativen Technologie ermöglicht octonomy eine hochqualitative und schnelle Automatisierung von Support Services – von Kundenanfragen bis hin zu internen Mitarbeiter- und Partneranfragen. Die Mission des Unternehmens:
Hochkomplexe Support‑Prozesse so einfach automatisierbar machen wie nie zuvor.