DevOps/MLOPs Engineer at dynamic AI/ Computer Vision company

Nomitri is a Berlin-based AI company at the forefront of Computer Vision and Edge AI. We build products that push the boundaries of what’s technically possible: running AI models in real time on resource-constrained devices, deployed in live retail environments across Europe.

Since January 2025, we are part of GK Software, Europe’s leading POS software provider, which is a wholly owned subsidiary of Fujitsu. This gives us the agility of a deep-tech startup with the long-term stability and global reach of an industry leader.

You’ll join a world-class engineering team (ex-Facebook, ex-Amazon, Cambridge, ex-Think-Cell, ex-Qualcomm, ex-ASML, and more) where you’ll solve novel problems in Edge AI, computer vision, scalable AI deployment, and cloud-edge infrastructure. Our mature and versatile tech stack allows us to prototype, iterate, and deploy new applications in weeks — but the challenges we tackle are often the first of their kind.

At Nomitri, you’ll have the chance to become a true expert in your field. We value curiosity, ownership, and fast learning. Every week you’ll see your work make an impact in real-world deployments.

We are based in Berlin and offer all new team members a hybrid work model from the start (3 days in-office, 2 days remote). We not only provide a dynamic workplace, but also a wide range of perks and benefits to support our employees’ well-being and growth.

Our long-term vision is clear: to become a worldwide leader in Edge AI and Computer Vision, starting with retail, and then expanding far beyond. If you’re looking to shape the future of AI at the edge, Nomitri is the place to grow.

The Role

We are looking for a highly skilled ML/DevOps Engineer to join our engineering team in Berlin. In this role, you will build and optimize the infrastructure that powers our cutting-edge AI products — from model training and deployment pipelines to cloud/on-prem orchestration and CI/CD automation.

You’ll work at the intersection of machine learning and systems engineering, ensuring that our Computer Vision models don’t just work in the lab but scale reliably in live retail environments across Europe. This is a hands-on role with direct ownership over systems that customers depend on every single day.

Why This Role Matters

As we expand our product portfolio and customer base, the reliability, scalability, and automation of our ML and deployment infrastructure become mission-critical. By joining us, you will:

• Streamline development with CI/CD pipelines that let us ship faster and safer.

• Boost AI productivity by improving ML workflows and model lifecycle management.

• Ensure reliability at scale through robust monitoring, networking, and security practices.

• Bridge the gap between ML and C++ systems, enabling smoother integration across our stack.

Your work will directly impact how quickly and reliably we can deliver innovation to our customers.

What You’ll Do

• Own and improve our CI/CD pipelines in GitLab for software and ML workflows.

• Manage ML experiments, model versioning, and deployment using MLFlow.

• Build and maintain containerized environments (Docker, Kubernetes) across development, staging, and production.

• Operate and optimize cloud and on-prem GPU infrastructure for ML training and inference.

• Automate workflows using Prefect or Airflow for training, data processing, and deployment pipelines.

• Define and maintain infrastructure as code with Terraform or Ansible.

• Contribute to system stability with Python and bash scripting for custom tooling and automation.

• Ensure secure networking, firewall, and access management across environments.

• Collaborate closely with ML researchers, C++ engineers, and product teams to ship models into production.

What You Bring (Must-Have Skills)

• Strong hands-on experience with MLFlow for experiment tracking and model lifecycle management.

• Deep knowledge of CI/CD implementation (GitLab CI/CD preferred).

• Proven expertise with Docker, Kubernetes, and containerized deployments.

• Solid experience managing cloud and on-prem GPU infrastructure.

• Hands-on experience with cloud production environments (GCP, AWS, or Azure).

• Solid grasp of infrastructure-as-code (Terraform, Ansible).

• Strong Python and bash scripting skills.

• Working knowledge of networking & security best practices (firewalls, access control, secure infra).

Nice to Have

• Experience deploying ML models at scale (serving, A/B testing).

• Proficiency with workflow orchestration tools (Prefect, Airflow, or similar).

• Monitoring skills with Prometheus, Grafana, and logging stacks.

• Familiarity with distributed computing frameworks (e.g. Ray).

• Data engineering experience (real-time pipelines, cleaning, transformation).

• Background in patch management for OS, hypervisors, and firmware.

• General familiarity with secrets management and secure Software Development Lifecycle practices.

Who You Are (Cultural Fit)

• Comfortable in a hybrid setup (3 days office / 2 days home).

• Thrive in a fast-learning environment solving hard problems.

• Take ownership of systems and keep them running smoothly.

• Proactive in planning upgrades and improvements before they become urgent.

• Ready to step in during critical incidents, even outside of core hours.

• Motivated by having direct impact and product ownership.

• Enjoy working in a DevOps-rich, collaborative, senior engineering team.

What We Offer

• The chance to shape the future of Edge AI and Computer Vision, with products already in production.

• A world-class engineering team (ex-Facebook, ex-Amazon, Cambridge, ex-Think-Cell, ex-Qualcomm, ex-ASML, and more).

• A culture that values impact over politics: flat, international, fast-moving, and respectful.

• Long-term stability as a wholly owned subsidiary of GK Software, Europe’s leading POS software provider.

• A Berlin-first culture with hybrid flexibility.