Dein persönlicher KI-Karriere-Agent
AI Engineer, Business and Engineering efficiency(m/w/x)
Designing and deploying production-grade machine learning systems to enhance business and engineering efficiency in automotive. 5+ years hands-on experience building and deploying production machine learning systems on cloud platforms required. Employer contribution towards pension plan.
Anforderungen
- Master’s degree in Computer Science, Machine Learning, or related field
- 5+ years of hands-on experience building and deploying ML systems in production environments
- Strong experience with cloud platforms (AWS, Azure) for data processing, training, and model deployment
- Proficiency in Python and core ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)
- Solid understanding of machine learning system design: pipelines, model lifecycle, performance tuning, and monitoring
- Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker)
- Familiarity with LLMs, prompting techniques, and inference strategies for GenAI solutions
- Strong software engineering skills: object-oriented design, version control, unit testing, and clean code principles
- Ability to work independently and collaboratively in a fast-paced, cross-functional environment
- Willingness to travel up to 10%, domestic and international travel
Aufgaben
- Design advanced machine learning systems
- Implement and productize ML solutions
- Translate business and technical requirements into ML solutions
- Deploy production-grade ML models and systems
- Conduct experiments and evaluate new algorithms
- Build and maintain data and ML pipelines
- Monitor and optimize ML systems for performance
- Contribute to MLOps practices and automated monitoring
- Collaborate with ML engineers, data scientists, and software engineers
- Stay current with ML/AI research and advancements
Berufserfahrung
- 5 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- AWS
- Azure
- Python
- PyTorch
- TensorFlow
- scikit-learn
- MLflow
- Kubeflow
- SageMaker
Benefits
Flexibles Arbeiten
- Flexible work schedule
Familienfreundlichkeit
- Good work-life balance
Attraktive Vergütung
- Competitive market base compensation
Betriebliche Altersvorsorge
- Employer contribution towards pension plan
Lockere Unternehmenskultur
- Diverse and inclusive work environment
Karriere- und Weiterentwicklung
- Career development opportunities
- Internal talent management programs
Weiterbildungsangebote
- Professional training
- Professional development opportunities
Mitarbeiterrabatte
- Employee discounts on products
Boni & Prämien
- Employee recognition and rewards program
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AI Engineer, Business and Engineering efficiency(m/w/x)
Designing and deploying production-grade machine learning systems to enhance business and engineering efficiency in automotive. 5+ years hands-on experience building and deploying production machine learning systems on cloud platforms required. Employer contribution towards pension plan.
Anforderungen
- Master’s degree in Computer Science, Machine Learning, or related field
- 5+ years of hands-on experience building and deploying ML systems in production environments
- Strong experience with cloud platforms (AWS, Azure) for data processing, training, and model deployment
- Proficiency in Python and core ML libraries (e.g., PyTorch, TensorFlow, scikit-learn)
- Solid understanding of machine learning system design: pipelines, model lifecycle, performance tuning, and monitoring
- Experience with MLOps tools and practices (e.g., MLflow, Kubeflow, SageMaker)
- Familiarity with LLMs, prompting techniques, and inference strategies for GenAI solutions
- Strong software engineering skills: object-oriented design, version control, unit testing, and clean code principles
- Ability to work independently and collaboratively in a fast-paced, cross-functional environment
- Willingness to travel up to 10%, domestic and international travel
Aufgaben
- Design advanced machine learning systems
- Implement and productize ML solutions
- Translate business and technical requirements into ML solutions
- Deploy production-grade ML models and systems
- Conduct experiments and evaluate new algorithms
- Build and maintain data and ML pipelines
- Monitor and optimize ML systems for performance
- Contribute to MLOps practices and automated monitoring
- Collaborate with ML engineers, data scientists, and software engineers
- Stay current with ML/AI research and advancements
Berufserfahrung
- 5 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- AWS
- Azure
- Python
- PyTorch
- TensorFlow
- scikit-learn
- MLflow
- Kubeflow
- SageMaker
Benefits
Flexibles Arbeiten
- Flexible work schedule
Familienfreundlichkeit
- Good work-life balance
Attraktive Vergütung
- Competitive market base compensation
Betriebliche Altersvorsorge
- Employer contribution towards pension plan
Lockere Unternehmenskultur
- Diverse and inclusive work environment
Karriere- und Weiterentwicklung
- Career development opportunities
- Internal talent management programs
Weiterbildungsangebote
- Professional training
- Professional development opportunities
Mitarbeiterrabatte
- Employee discounts on products
Boni & Prämien
- Employee recognition and rewards program
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
0100 Harman Becker Automotive Systems GmbH
Branche
Automotive
Beschreibung
HARMAN is a technology leader focused on innovation, inclusivity, and teamwork, providing cutting-edge solutions in the automotive and connected ecosystem.
Noch nicht perfekt?
- VESTIGAS
(Senior) AI Engineer / MLOps Engineer(m/w/x)
Vollzeitmit HomeofficeSeniorMünchen - OMMAX
(Senior) AI Engineer(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenMünchen - Analog Devices, Inc.
Staff AI Engineer(m/w/x)
Vollzeitmit HomeofficeSeniorMünchen - appliedAI Initiative GmbH
AI Engineer - Focus: Software Engineering(m/w/x)
Vollzeitmit HomeofficeBerufserfahrenHeilbronn, München - OMMAX
Lead AI Engineer(m/w/x)
Vollzeitmit HomeofficeSeniorMünchen