Who needs your support? noimos is a Zurich-based, but globally focused, start-up harnessing the potential of ML, computer vision and design to shake up the insurance industry and revolutionize the all-important claims process. We are an independent subsidiary of one of the largest insurance groups in the world, AXA, enjoying many of the benefits that that brings. From a personal point of view, noimos is a small group of experienced professionals, with strong background in technology, entrepreneurship, and insurance. We are passionate about making a difference with our products and enjoying ourselves along the way. The challenges we tackle at noimos are diverse, demanding, and meaningful. Shape Our MLOps Infrastructure Design, implement, and maintain MLOps infrastructure on GCP (Terraform, Pub/Sub, Vertex AI, CI/CD, GitHub Actions) to ensure scalability, automation, and reliability. Act as a Subject Matter Expert for MLOps and infrastructure, setting best practices and guiding the team in deploying and maintaining ML models in production. Build and optimize CI/CD pipelines for efficient training, serving, and monitoring of ML models, ensuring seamless operations at scale. Work within the ML engineering team, focusing on productionizing ML models, optimizing inference pipelines, and ensuring long-term model stability. Serve as the bridge between the ML team and the software development team, ensuring smooth integration of infrastructure and ML workflows. Take part in core ML engineering tasks, such as managing model inference pipelines, monitoring performance, and ensuring model stability in production. Contribute hands-on with Python development, focusing on automation, infrastructure, and tooling. Our tech stack includes: Infrastructure (GCP, Vertex AI, Cloud Run, Terraform, GPU, Docker, GitHub Actions, CI/CD) Python and computer vision libraries (e.g. NumPy, pandas, OpenCV, scikit-image) Frameworks associated with training and evaluation of image recognition tasks (PyTorch) Databases (SQL, BigQuery) Your Toolkit for MLOps Mastery You have 2 years of experience with DevOps and MLOps concepts, ideally using GitHub workflows, with a strong focus on infrastructure scalability and automation. Furthermore, you gained 5 years of experience in data science or software engineering projects, with a particular focus on Deep Learning and Computer Vision, including deploying and maintaining ML models in production. You enrich your team with strong programming skills in Python, incl. clean/modular and production-ready code. You are experienced in working with large data sets and in building auto-scaling ML systems & MLOps. Ability to guide and mentor teams, assign tasks, and foster an environment of collaboration and efficiency. Ideally, you are proficient at using GCP (including Pub/Sub, Vertex), CI/CD practices, GitHub Actions, Terraform, and pipeline automation. You are proficient in English. Benefits 5 weeks vacation Choose your hardware Typical office hours with flexibility Bike room and showers Home office / remote working 2 days per week International team Part time possible Bonus payment Air conditioning and standing desk Very good pension fund/or solutions Well-connected office Startup culture & convivial team events Andjela Zdravkovic