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Job details
Company
compredict
Location
Darmstadt, Germany
Employment type
Full-time
Seniority
Mid level
Primary category
DevOps & SRE
Secondary category
Machine Learning & AI
Posted date
29 Oct 2025
Valid through
28 Dec 2025
Job description
Your mission
As an MLOps Engineer, you will play a critical role in ensuring our machine learning models transition seamlessly from research to production. These models analyze car data over time to generate actionable insights, a couple examples of COMPREDICT portfolio:- Predicting tire pressure without traditional sensors.
- Predict the correct angle of vehicle’s front headlights to provide optimal visibility for the driver without blinding oncoming traffic.
Your Role in More Detail:
MLOps Pipeline Development and Optimization:
- Design and maintain scalable pipelines for deploying machine learning models whether in-cloud or in-vehicle.
- Ensure models are securely integrated into production environments with minimal latency.
- Implement monitoring systems to track model performance and flag issues.
- Develop methods to evaluate and compare the performance of different models.
- Automate processes for validating model accuracy and consistency in production.
- Work closely with data scientists, developers, and stakeholders to understand their needs and provide tailored solutions.
- Effectively communicate technical processes and outcomes to both technical and non-technical audiences.
- Create comprehensive documentation for processes, pipelines, and workflows.
- Provide training and guidance to team members on MLOps best practices.
Your profile
- At least 2 years working experiences in modern DevOps practices and microservice architecture.
- Expertise in Kubernetes and containerization technologies.
- Hands-on experience with platforms such as KubeFlow, Kserve, or equivalent.
- Experience in ML Experimentation and registry platforms such as W&B or MLFLow.
- Understanding of time series modeling and its data requirements.
- Familiar with ML/NN frameworks.
- Familiar with AWS or other cloud service providers is a plus.
- Strong ability to collaborate with cross-functional teams, including data scientists, engineers, and clients.
- Clear and concise in verbal and written communication, with excellent documentation skills.
- Fluent in both written and spoken English. German is a plus.