ML Platform Engineer | Zurich OR Fribourg | Switzerland

pbWork Model: /bHybrid – 3 days in officebr/ppbContract Type: /bPermanentbr/ppbResponsibilities /bbr/pulliDesign, develop, test, and maintain AI/ML infrastructure within a scalable microservices architecture running on Kubernetes.br/liliBuild and maintain high-quality, secure, and reliable DevOps pipelines and Helm chartsbr/liliWork across the backend stack, integrating event-driven systems (Kafka), gRPC services, and REST APIsbr/liliDevelop and optimize data pipelines using modern data engineering tools (e.g., Spark)br/liliManage ML lifecycle processes using tools such as MLflowbr/liliContribute to architectural decisions to improve scalability, performance, and system reliabilitybr/liliSupport deployment and monitoring of ML models in complex production environments, including isolated (air-gapped) setups with varying hardware constraints (CPU/GPU).br/liliEnsure platform reliability and robustness in customer-deployed Kubernetes environmentsbr/liliMaintain high security and compliance standards aligned with industry best practices (e.g., ISO 27001br/li /ulh3Requirements /h3ulliDegree in Computer Science, Engineering, or equivalent practical experiencebr/lili5+ years of experience in AI/ML platform engineering or related rolesbr/liliStrong experience with Kubernetes, distributed systems, and data engineering technologiesbr/liliHands-on experience with ML platforms and frameworks (e.g., MLflow, PyTorch, SparkML)br/liliFamiliarity with modern data stack technologies (e.g., Spark, Delta Lake, TensorFlow, ONNX)br/liliExperience building clean, maintainable, and testable systems following modern software engineering principlesbr/liliKnowledge of cloud-native development and DevOps practices (including Helm)br/liliExperience working in security-sensitive or highly regulated environments is a plus.br/liliStrong problem-solving and debugging skillsbr/liliExcellent communication skills in English and ability to collaborate across teamsbr/li /ul #J-18808-Ljbffr