MLOps Engineer

This is a fully remote position, open to applicants in Germany.

📋 Description

• Design and maintain scalable pipelines for deploying machine learning models, whether in the cloud or in vehicles.

• Ensure that models are securely integrated into production environments with minimal latency.

• Implement monitoring systems to track model performance and identify issues.

• Develop methodologies to assess and compare the performance of various models.

• Automate processes for validating model accuracy and consistency in production settings.

• Collaborate closely with data scientists, developers, and stakeholders to comprehend their needs and deliver customized solutions.

• Communicate technical processes and outcomes effectively to both technical and non-technical audiences.

• Create detailed documentation for processes, pipelines, and workflows.

• Provide training and support to team members on MLOps best practices.

⛳️ Requirements

• A minimum of 2 years of experience in modern DevOps practices and microservice architecture.

• Proficiency in Kubernetes and containerization technologies.

• Practical experience with platforms such as KubeFlow, Kserve, or similar.

• Experience with ML experimentation and registry platforms like W&B or MLFlow.

• Knowledge of time series modeling and its data requirements.

• Familiarity with ML/NN frameworks.

• Experience with AWS or other cloud service providers is a bonus.

• Strong collaborative skills to work with cross-functional teams, including data scientists, engineers, and clients.

• Ability to communicate clearly and concisely in both verbal and written forms, with excellent documentation capabilities.

• Proficient in both written and spoken English; German language skills are a plus.

🏝️ Benefits

• Opportunities for professional development.