Machine Learning Engineer - Köln

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 ...

Jobbeschreibung

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.

Your Role
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, andoperateML 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,establishbest practices, and mentor others as we scale our AI engineering organization.

Your Profile

• 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 beyondinitialtraining.
• Leadership and project ownership: Proven ability to lead complex technical projects end-to-end (Staff/Principal mindset is a strong plus).

Why us

• 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)

Über uns

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.

Your mission

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.

Your Role
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, andoperateML 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,establishbest practices, and mentor others as we scale our AI engineering organization.

Your profile

• 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 beyondinitialtraining.
• Leadership and project ownership: Proven ability to lead complex technical projects end-to-end (Staff/Principal mindset is a strong plus).

Why us?

• 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)

About us

Let's build the future of work — together. Seriously

At octonomy, you can expect an environment that values quality, encourages creativity, and delivers real, measurable results. If you're excited to bring AI into everyday business in a practical way and grow with us, we'd love to get to know you.

Feel free to reach out with a short note or a full application — what matters most is that you're keen to help shape what we're building. | We grow output. Not headcount.

Questions about the role or your application? Contact Mia from our HR team at octonomy-ai-