ML Platform Engineer | Zurich OR Fribourg | Switzerland

Acquism SARL; Zürich; Hybrid; CHF 140,000 - 210,000; Full time

Job summary

Acquism SARL in Zürich is seeking an experienced AI/ML platform engineer to design, build, test, and operate scalable ML infrastructure within Kubernetes-based microservices. The role emphasizes DevOps, data pipelines, and secure, compliant production environments.

You will collaborate across teams, own ML lifecycle tooling (MLflow, PyTorch, Spark), and support air-gapped deployments with varying hardware constraints while maintaining ISO 27001-aligned security standards.

Qualifications

• 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 and distributed systems.
• Excellent communication in English and collaboration across teams.

Responsibilities

• Design, develop, test, and maintain AI/ML infrastructure within Kubernetes.
• Build and maintain secure DevOps pipelines and Helm charts.
• Integrate event-driven systems (Kafka), gRPC, and REST APIs.
• Develop data pipelines using Spark and related tools.
• Manage ML lifecycle with MLflow.
• Enhance scalability, performance, and reliability of platforms.
• Support deployment and monitoring in air-gapped production environments.
• Ensure ISO 27001-aligned security and compliance.

Skills

AI/ML platform engineering

Kubernetes

Distributed systems

Data engineering

Problem solving

English communication

Education

Degree in Computer Science, Engineering, or equivalent practical experience

Tools

Kubernetes

MLflow

PyTorch

SparkML

Spark

Delta Lake

TensorFlow

ONNX

gRPC

REST APIs

Kafka

Helm

Job description

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