PpAlgorized is a VC-funded Silicon Valley deep-tech company with Swiss roots building edge‑AI models that give robots real‑time human awareness using existing wireless sensors -enabling safer human‑machine co‑presence. /p pAs we continue to scale rapidly, we are looking for a DevOps/MLOps Engineer for our office at Etoy, Switzerland who is genuine passionate about innovation, product development and building robust systems end‑to‑end. If you thrive in dynamic startup environment, take ownership, and know to seamlessly connect backend, frontend, and embedded systems, we’d love to meet you. /p h3Responsibilities /h3 ul liDrive, design and own development of platformto deliverdata based onactionable insights /li liEnd to end responsibility for the technical requirements, design, development, integration and verification of platform‑based solution that uses machine learning to analyze large datasets /li liSelect,designand implement suitable cloud databases for slow and fast data storage with emphasis on scalability, reliability and performance /li liOptimize the ML algorithms to ensure high performance and reliability /li liDevelop APIstrategy, APIsanddesign pathways to integrate with customer systems /li liCreate and maintain a CI/CDinfrastructure thatsupports the scaling of the AWS‑based platform /li liProvide and maintain tooling, templates, and best practices to standardize development, deployment, and ML workflows /li liMonitor, troubleshoot, and continuously improve production systems, CI/CD workflows, and ML pipelines, with a focus on performance, security, and cost /li liActively participate in software development and integration of real time solutions /li liClose collaboration with the team on the development process, including defining goals and ensuring milestones delivery in a high cross‑functional capacity as per customer’s needs /li liMSc or advanced degree in a relevant field with 5+ years of experience in MLOps, ML model deployment, and cloud infrastructure /li liStrong hands‑on experience with AWS services (e.g. EC2, S3, IAM, ECR, ECS/EKS, SageMaker) /li liProven experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar) /li liStrong proficiency with Linux, scripting, and automation (Bash, Python) /li liExperience with containerized environments (Docker; Kubernetes is a plus) /li liPractical experience supporting machine learning workflows, including training, model versioning, and deployment /li liStrong problem‑solving and communication skills, with the ability to document systems and workflows clearly /li /ul h3Preferred Requirements /h3 ul liExperience with Infrastructure as Code tools (Terraform, CloudFormation, or equivalent) /li liExperience with embedded real times system is a huge plus /li /ul /p #J-18808-Ljbffr