ML Platform Engineer | Zurich OR Fribourg | Switzerland

Zürich - Switzerland

Monthly Salary: Not Disclosed

Experience Required: 4-6years

Posted on: 7 hours ago

Vacancies: 1 Vacancy

Job Summary

Location: Zurich OR Fribourg (Switzerland)

Work Model: Hybrid 3 days in office

Contract Type: Permanent

Responsibilities

Design develop test and maintain AI/ML infrastructure within a scalable microservices architecture running on Kubernetes.
Build and maintain high-quality secure and reliable DevOps pipelines and Helm charts
Work across the backend stack integrating event-driven systems (Kafka) gRPC services and REST APIs
Develop and optimize data pipelines using modern data engineering tools (e.g. Spark)
Manage ML lifecycle processes using tools such as MLflow
Contribute to architectural decisions to improve scalability performance and system reliability
Support deployment and monitoring of ML models in complex production environments including isolated (air-gapped) setups with varying hardware constraints (CPU/GPU).
Ensure platform reliability and robustness in customer-deployed Kubernetes environments
Maintain high security and compliance standards aligned with industry best practices (e.g. ISO 27001

Requirements

Degree in Computer Science Engineering or equivalent practical experience
5 years of experience in AI/ML platform engineering or related roles
Strong experience with Kubernetes distributed systems and data engineering technologies
Hands-on experience with ML platforms and frameworks (e.g. MLflow PyTorch SparkML)
Familiarity with modern data stack technologies (e.g. Spark Delta Lake TensorFlow ONNX)
Experience building clean maintainable and testable systems following modern software engineering principles
Knowledge of cloud-native development and DevOps practices (including Helm)
Experience working in security-sensitive or highly regulated environments is a plus.
Strong problem-solving and debugging skills
Excellent communication skills in English and ability to collaborate across teams

Required Skills:

Degree in Computer Science Engineering or equivalent practical experience 5 years of experience in AI/ML platform engineering or related roles Strong experience with Kubernetes distributed systems and data engineering technologies Hands-on experience with ML platforms and frameworks (e.g. MLflow PyTorch SparkML) Familiarity with modern data stack technologies (e.g. Spark Delta Lake TensorFlow ONNX) Experience building clean maintainable and testable systems following modern software engineering principles Knowledge of cloud-native development and DevOps practices (including Helm) Experience working in security-sensitive or highly regulated environments is a plus. Strong problem-solving and debugging skills Excellent communication skills in English and ability to collaborate across teams

Location: Zurich OR Fribourg (Switzerland)Work Model: Hybrid 3 days in officeContract Type: PermanentResponsibilitiesDesign develop test and maintain AI/ML infrastructure within a scalable microservices architecture running on Kubernetes.Build and maintain high-quality secure and reliable DevOps pi...