Machine Learning Ops Engineer

Build the bridge from model to production.

  • Porto
  • Permanent
  • IT
  • 01.05.2026
  • Full-time

 

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Love what you do – we make employment happen!

Are you a passionate MLOps Engineer eager to take on a new challenge that has the potential to revolutionize the European Job Ads Market? Then keep reading!

Great models are worthless if they never make it into production. That's where you come in: as our MLOps Engineer, you build the infrastructure that turns prototypes into reliable, scalable systems serving millions of job seekers. You'll design end-to-end ML pipelines, keep models fast and stable in production, and set the standards our data scientists build on. Kubernetes, CI/CD, LLM frameworks and cloud platforms are your daily tools, not buzzwords. If you love automation and take pride in systems that just work, keep reading.

This is us: You've surely heard of jobs.ch. This is just one of the many brands owned by JobCloud. We are the leading player in Switzerland’s online job market and want to make job search and recruitment as easy as possible. Love what you do – we make employment happen!

By the way: We don't care about your skin colour, your gender identity or your beliefs... Come as you are, you are just good.

YOUR TASKS

  • Design, build, and maintain end-to-end ML pipelines from data ingestion to model deployment and monitoring
  • Collaborate with data scientists and cloud engineers to productionize ML models and establish best practices
  • Develop and maintain model serving infrastructure with focus on scalability, reliability, and low latency
  • Manage ML experiment tracking, model versioning, and model registry systems
  • Monitor model performance in production and implement alerting systems
  • Implement security best practices for ML systems and ensure compliance with data governance policies
  • Document MLOps processes, architecture decisions, and runbooks

YOUR SKILLS

  • 5+ years of experience in MLOps, DevOps, or related production ML roles, including deploying ML/AI prototypes into production
  • Strong experience with cloud platforms (AWS, GCP, or Azure) and cloud data warehouses, SQL/NoSQL databases and real-time data pipelines
  • Hands-on experience with container orchestration (Kubernetes, ECS, or similar)
  • Proficiency with CI/CD pipelines, Infrastructure as Code, and version control
  • Hands-on experience with modern ML frameworks (PyTorch, TensorFlow, or similar); familiarity with LLM frameworks, vector databases, and RAG architectures is a plus
  • Passion for automation and building reliable, well-crafted systems
  • Excellent communication skills and ability to work cross-functionally in an independent, self-organized way

OUR OFFER

BENEFITS
  • 10 days fully paid sick leave per year
  • 25 days of annual vacation leave
  • Full private health coverage (employee + up to 2 children to age 20)
  • Gym allowance
  • Hybrid & flexible working (team-based arrangement)
 

 

YOUR CONTACT PERSON

Our Hiring Process

  • Presentation of the project and company ~ 30 mins
  • Conversation with hiring manager ~ 1 hour
  • Technical challenge (at your best convenience)
  • Challenge presentation ~1h-1.5 hour
  • Offer
Ms Marina Faria
Marina Faria
Senior Talent Acquisition Partner
+41 79 349 32 51