MLOps/DevOps Engineer

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.

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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

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• 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

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• Select, design and implement suitable cloud databases for slow and fast data storage with emphasis on scalability, reliability and performance

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• Optimize the ML algorithms to ensure high performance and reliability

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• Develop API strategy, APIs and design pathways to integrate with customer systems

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• Create and maintain a CI/CD infrastructure that supports the scaling of the AWS-based platform

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• Provide and maintain tooling, templates, and best practices to standardize development, deployment, and ML workflows

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• Monitor, troubleshoot, and continuously improve production systems, CI/CD workflows, and ML pipelines, with a focus on performance, security, and cost

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• Actively participate in software development and integration of real time solutions

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• 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

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• Strong hands-on experience with AWS services (e.g. EC2, S3, IAM, ECR, ECS/EKS, SageMaker)

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• Proven experience designing and maintaining CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar)

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• Strong proficiency with Linux, scripting, and automation (Bash, Python)

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• Experience with containerized environments (Docker; Kubernetes is a plus)

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• Practical experience supporting machine learning workflows, including training, model versioning, and deployment

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• 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)

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• Experience with embedded real times system is a huge plus

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• Coding in C/C++