Machine Learning Ops Engineer
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WHAT ARE 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
WHAT QUALIFICATIONS DO WE REQUIRE?
2-3 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
Strong hands-on experience investigating and resolving ML workload failures in Linux environments using standard process, resource, logging, filesystem, service-management, and networking tools
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
Full professional proficiency in English
WHAT DO WE OFFER?
1 day per month to tackle challenges inside the project, or test new ideas
Tech training and human skills training and, budget for conferences
Opportunity to travel and collaborate in our various office locations for workshops or team-building events (Zurich, Geneva, Belgrade or Vienna)
A dynamic work environment that highly fosters a sense of fun while maintaining a productive atmosphere
Our Hiring ProcessVideo Call with People & Culture (30 mins)
Video Call with hiring manager (1 hour)
Technical challenge (at your best convenience)
Challenge presentation by video call (1h-1.5 hour)
Offer
WHAT ARE OUR 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)
Learning & Development
Workation
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