PROFI Engineering Systems AG
Machine Learning Engineer(m/w/x)
Vollzeitmit HomeofficeBerufserfahren
Darmstadt
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COCOMPREDICT
MLOps Engineer(m/w/x)
Darmstadt
Vollzeitmit HomeofficeBerufserfahren
Nejo KI-Zusammenfassung
ML model deployment pipelines for software-defined vehicles at sustainable mobility solutions provider. Kubernetes, KubeFlow/Kserve, and ML Experimentation platforms experience required. Focus on secure, low-latency in-vehicle ML integration.
Anforderungen
- Proficiency in modern DevOps practices and microservice architecture
- Expertise in Kubernetes and containerization technologies
- Hands-on experience with 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
- Familiarity with ML/NN frameworks
- Familiarity with AWS or other cloud service providers
- Strong collaboration skills with cross-functional teams
- Clear and concise verbal and written communication
- Fluency in written and spoken English; German is a plus
Aufgaben
- Design and maintain scalable pipelines for deploying machine learning models in-cloud or in-vehicle
- Ensure secure integration of models 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
- Collaborate with data scientists, developers, and stakeholders to understand their needs
- Communicate technical processes and outcomes to technical and non-technical audiences
- Create comprehensive documentation for processes, pipelines, and workflows
- Provide training and guidance on MLOps best practices
Berufserfahrung
- 2 - 5 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
- Deutsch – Grundkenntnisse
Tools & Technologien
- Kubernetes
- KubeFlow
- Kserve
- W&B
- MLFLow
- AWS
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens COMPREDICT erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
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COCOMPREDICT
MLOps Engineer(m/w/x)
Darmstadt
Vollzeitmit HomeofficeBerufserfahren
Nejo KI-Zusammenfassung
ML model deployment pipelines for software-defined vehicles at sustainable mobility solutions provider. Kubernetes, KubeFlow/Kserve, and ML Experimentation platforms experience required. Focus on secure, low-latency in-vehicle ML integration.
Anforderungen
- Proficiency in modern DevOps practices and microservice architecture
- Expertise in Kubernetes and containerization technologies
- Hands-on experience with 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
- Familiarity with ML/NN frameworks
- Familiarity with AWS or other cloud service providers
- Strong collaboration skills with cross-functional teams
- Clear and concise verbal and written communication
- Fluency in written and spoken English; German is a plus
Aufgaben
- Design and maintain scalable pipelines for deploying machine learning models in-cloud or in-vehicle
- Ensure secure integration of models 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
- Collaborate with data scientists, developers, and stakeholders to understand their needs
- Communicate technical processes and outcomes to technical and non-technical audiences
- Create comprehensive documentation for processes, pipelines, and workflows
- Provide training and guidance on MLOps best practices
Berufserfahrung
- 2 - 5 Jahre
Ausbildung
- Bachelor-AbschlussODER
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
- Deutsch – Grundkenntnisse
Tools & Technologien
- Kubernetes
- KubeFlow
- Kserve
- W&B
- MLFLow
- AWS
Die Originalanzeige dieses Stellenangebotes in der aktuellsten Version findest du hier. Nejo hat diesen Job automatisch von der Website des Unternehmens COMPREDICT erfasst und die Informationen auf Nejo mit Hilfe von KI für dich aufbereitet. Trotz sorgfältiger Analyse können einzelne Informationen unvollständig oder ungenau sein. Bitte prüfe immer alle Angaben in der Originalanzeige! Inhalte und Urheberrechte der Originalanzeige liegen beim ausschreibenden Unternehmen.
Über das Unternehmen
COMPREDICT
Branche
Automotive
Beschreibung
The company is driving the shift towards software-defined vehicles, offering solutions for sustainable mobility.
Noch nicht perfekt?
- PROFI Engineering Systems AG
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Vollzeitmit HomeofficeSeniorDarmstadt