MLOps/DevOps Engineer

Algorized

Campbell, California, United States

Campbell, California, United States

Über

Company Description Algorized 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. As we continue to scale rapidly, we are looking for a DevOps/MLOps Engineer for our office at Campbell, California 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. Responsibilities Drive, design and own development of platform to deliver data based on actionable insights End to end responsibility for the technical requirements, design, development, integration and verification of platform-based solution that uses machine learning to analyze large datasets Select, design and implement suitable cloud databases for slow and fast data storage with emphasis on scalability, reliability and performance Optimize the ML algorithms to ensure high performance and reliability Develop API strategy, APIs and design pathways to integrate with customer systems Create and maintain a CI/CD infrastructure that supports the scaling of the AWS-based platform Provide and maintain tooling, templates, and best practices to standardize development, deployment, and ML workflows Monitor, troubleshoot, and continuously improve production systems, CI/CD workflows, and ML pipelines, with a focus on performance, security, and cost Actively participate in software development and integration of real time solutions Close 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 Minimum Requirements MSc or advanced degree in a relevant field with 5+ years of experience in MLOps, ML model deployment, and cloud infrastructure Strong hands-on experience with AWS services (e.g. EC2, S3, IAM, ECR, ECS/EKS, SageMaker) Proven experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar) Strong proficiency with Linux, scripting, and automation (Bash, Python) Experience with containerized environments (Docker; Kubernetes is a plus) Practical experience supporting machine learning workflows, including training, model versioning, and deployment Strong problem-solving and communication skills, with the ability to document systems and workflows clearly Preferred Requirements Experience with Infrastructure as Code tools (Terraform, CloudFormation, or equivalent) Experience with embedded real times system is a huge plus Coding in C/C++

Campbell, California, United States

Sprachkenntnisse

English

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