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DevOps/MLOps Engineer

Algorized
Etoy, VD

Jetzt bewerben

Details zur Stelle

100% | Pensum: 90-100%

Qualifikationen

CI/CD
Master
Bash
AWS
C++
Docker
Terraform
Scripting
GitHub
S3
Linux
GitLab
Kommunikationsfähigkeit
Python

Vollständige Stellenbeschreibung

DevOps/MLOps Engineer

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 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.

LOCATION

On-Site/Switzerland

EMPLOYMENT TYPE

Full Time

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

Qualifications

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++

Jetzt bewerben

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