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.

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.

This turns us into the perfect employer

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

5 steps until your welcome party

  • You apply via the web form
  • You meet with a recruiter
  • You get to know your supervisor from your department
  • You receive a contract offer
  • Welcome to the team

Ready to scale MLOps with us? Apply now!

If you’re eager to experiment, explore, and make a real impact, we’d love to hear from you. Apply now and let’s shape the future together!

Andjela Zdravkovic

Relationship Manager

Contact & Apply

Senior DevOps Engineer (MLOps, Infrastructure)

Transparency and open communication are important to us. We, noimos ag (the hiring company, hereinafter referred to as "Company") would therefore like to point out to you that parts of our recruitment process are provided by a specialised, external service provider (digitalent ag, hereinafter referred to as "Service Provider").

For the purpose of handling the recruitment process, the service provider collects and processes the personal data of interested parties and applicants. The processing can take place electronically. This is particularly the case if a prospective candidate submits corresponding application documents electronically, for example by e-mail or via a web form on the website. In the case of an application, the service provider transmits the following data to the company:

  • contact details
  • First name, last name
  • Curriculum vitae if applicable
  • Certificates, if applicable
  • all data transmitted by yourself for this purpose, such as the qualifications, work experience, preferences, etc. provided.

If the company concludes an employment contract with an applicant, the transferred data will be stored for the purpose of processing the employment relationship in compliance with the statutory provisions. If no employment contract is concluded between the company and the applicant, the application documents will be deleted six months after notification of the rejection decision latest, provided that no other legitimate interests or contractual obligations are opposed to deletion.

Furthermore, the data protection regulations of the service provider also apply.

We already work with selected recruitment specialists and only accept direct applications. Should we receive applications through personnel service providers, we will treat these as direct applications. We do not plan to expand our supplier base or enter into any other contract with recruitment agencies.

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