PROFI Engineering Systems AG
Machine Learning Engineer(m/w/x)
Full-timeWith HomeofficeExperienced
Darmstadt
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COCOMPREDICT
MLOps Engineer(m/w/x)
Darmstadt
Full-timeWith Home OfficeExperienced
Nejo AI Summary
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.
Requirements
- 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
Tasks
- 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
Work Experience
- 2 - 5 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
- German – Basic
Tools & Technologies
- Kubernetes
- KubeFlow
- Kserve
- W&B
- MLFLow
- AWS
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of COMPREDICT and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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COCOMPREDICT
MLOps Engineer(m/w/x)
Darmstadt
Full-timeWith Home OfficeExperienced
Nejo AI Summary
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.
Requirements
- 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
Tasks
- 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
Work Experience
- 2 - 5 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
- German – Basic
Tools & Technologies
- Kubernetes
- KubeFlow
- Kserve
- W&B
- MLFLow
- AWS
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of COMPREDICT and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
COMPREDICT
Industry
Automotive
Description
The company is driving the shift towards software-defined vehicles, offering solutions for sustainable mobility.
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