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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.
Requirements
- 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
Tasks
- 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
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- AWS
- Azure
- Python
- PyTorch
- TensorFlow
- scikit-learn
- MLflow
- Kubeflow
- SageMaker
Benefits
Flexible Working
- Flexible work schedule
Family Support
- Good work-life balance
Competitive Pay
- Competitive market base compensation
Retirement Plans
- Employer contribution towards pension plan
Informal Culture
- Diverse and inclusive work environment
Career Advancement
- Career development opportunities
- Internal talent management programs
Learning & Development
- Professional training
- Professional development opportunities
Corporate Discounts
- Employee discounts on products
Bonuses & Incentives
- 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.
Requirements
- 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
Tasks
- 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
Work Experience
- 5 years
Education
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- AWS
- Azure
- Python
- PyTorch
- TensorFlow
- scikit-learn
- MLflow
- Kubeflow
- SageMaker
Benefits
Flexible Working
- Flexible work schedule
Family Support
- Good work-life balance
Competitive Pay
- Competitive market base compensation
Retirement Plans
- Employer contribution towards pension plan
Informal Culture
- Diverse and inclusive work environment
Career Advancement
- Career development opportunities
- Internal talent management programs
Learning & Development
- Professional training
- Professional development opportunities
Corporate Discounts
- Employee discounts on products
Bonuses & Incentives
- Employee recognition and rewards program
About the Company
0100 Harman Becker Automotive Systems GmbH
Industry
Automotive
Description
HARMAN is a technology leader focused on innovation, inclusivity, and teamwork, providing cutting-edge solutions in the automotive and connected ecosystem.
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