xorika

Machine Learning Engineer

Zurich, Switzerland (Remote)Full-timeSenior

Overview

Join our Zurich engineering hub to design and deploy production machine learning systems that power our clients' most critical AI initiatives. You'll work at the intersection of research and applied engineering, turning cutting-edge models into scalable, reliable services.

Key Responsibilities

  • Design, train, and deploy ML models for real-world enterprise applications
  • Build and maintain robust ML pipelines for data processing, training, and serving
  • Collaborate with AI researchers and product engineers to translate prototypes into production systems
  • Optimize model performance, latency, and cost across cloud and on-premise environments
  • Contribute to internal ML tooling and best practices documentation

Requirements

Essential

  • 4+ years of experience in machine learning engineering
  • Strong proficiency in Python and ML frameworks (PyTorch, JAX, or TensorFlow)
  • Experience deploying ML models at scale in production environments
  • Solid understanding of MLOps practices and tooling (MLflow, Kubeflow, or similar)
  • Fluent in English; German is a plus

Preferred

  • Experience with NLP, computer vision, or time-series forecasting
  • Familiarity with cloud ML services (AWS SageMaker, GCP Vertex AI, Azure ML)
  • Publications or contributions to the ML research community
  • Experience working in regulated industries (finance, healthcare, pharma)

Benefits

  • Competitive Swiss salary and annual bonus
  • Comprehensive health and accident insurance
  • 25 days paid vacation plus Swiss public holidays
  • Pension fund (BVG) contribution above statutory minimum
  • Annual learning and conference budget
  • Relocation support for international candidates

Our Team Culture

Our Zurich team brings together world-class engineers in one of Europe's top tech hubs. We value deep technical craft, open collaboration, and a healthy work-life balance. You'll have the autonomy to drive meaningful projects while learning from peers with diverse backgrounds.