Software Engineer 80–100% - Senior AWS & MLOps Engineer

(Senior) Software Engineer (m/f) 80–100% - Senior AWS & MLOps Engineer Successful with AutoForm! AutoForm offers software solutions for sheet metal forming and BiW assembly process. With over 500 employees dedicated to this field, AutoForm is recognized as the leading provider of software for product manufacturability, tool and material cost calculation, die face design and virtual stamping as well as BiW assembly process optimization. All of the Top 20 automotive OEMs and most of their suppliers have selected AutoForm as their software of choice. Besides its headquarters in Switzerland, AutoForm has offices in Germany, The Netherlands, France, Spain, Italy, Czech Republic, Sweden, USA, Mexico, Brazil, India, China, Japan and Korea. To support the growth of our Software Development Department in Zürich, we are looking for a (Senior) Software Engineer (m/f) 80–100% Senior AWS & MLOps Engineer AutoForm is building a next-generation Application Platform to support and scale innovative AI-powered cloud applications. To strengthen our cloud and AI platform capabilities, we are looking for an experienced engineer with deep practical expertise in Amazon Web Services (AWS) and modern MLOps platforms. This is not a data science role. We are looking for a software and platform engineer who enjoys building and operating cloud infrastructure, AI platforms, and production-grade machine learning environments. Your tasks As a Senior AWS & MLOps Engineer, you will: Design, implement, and operate cloud-native AI and MLOps infrastructure on AWS Develop and maintain deployment pipelines for AI-powered applications and services Support model training, serving, monitoring, and lifecycle management in production environments Design scalable cloud architectures for machine learning workloads Implement Infrastructure as Code using tools such as CDK, CloudFormation, or Terraform Operate and improve containerized environments using Kubernetes and related technologies Support AI and data engineering teams with platform services, tooling, and best practices Contribute to observability, reliability, security, and cost optimization initiatives Evaluate and integrate emerging AWS and MLOps technologies where appropriate Collaborate closely with product teams and platform colleagues in a SCRUM-based setup