Dein persönlicher KI-Karriere-Agent
Senior ML Engineer(m/w/x)
Automated pipeline optimization and reinforcement learning for automotive sensor platforms. Ph.D. in computer science or machine learning required. 30 days vacation, overtime compensation.
Anforderungen
- Ph.D. in computer science, machine learning, or related field, or master degree with extensive experience
- Excellent analytical skills and mathematical background
- Professional experience in two specific areas
- Knowledge of deep neural networks and ML techniques
- Knowledge of reinforcement learning techniques
- Experience in time series prediction with RNN
- Knowledge of SOTA ML techniques and transformers
- Experience in generative, foundation, and language models
- Systematic, goal and outcome oriented working style
- Professional experience in PyTorch
- Professional skills in Python and C++
- Oral and written English skills
- Experience in datasets and data science methods
- Understanding of edge processing and RUST
- Experience in team software development and Git
- Proven track record of scientific publications
Aufgaben
- Develop and evaluate machine learning models using supervised, unsupervised, and reinforcement learning
- Conduct thorough model evaluation and validation using performance metrics
- Ensure model accuracy, reliability, and robustness
- Implement and optimize automated machine learning pipelines and frameworks
- Streamline model development, training, and deployment processes
- Automate feature engineering, model selection, and hyperparameter tuning
- Deploy and scale machine learning models on AWS, Azure, or Google Cloud
- Leverage cloud-based services for data storage, processing, and analysis
- Implement CI/CD pipelines for automated model deployment, testing, and monitoring
- Integrate AI/ML solutions into existing software development workflows
- Design AI/ML solutions following automotive product development standards
- Collaborate with cross-functional teams to align with product requirements
- Design and conduct A/B tests to evaluate real-world model impact
- Analyze test results to provide data-driven optimization recommendations
- Orchestrate ML workflows using Kubeflow Pipelines in Kubernetes environments
- Automate build, test, and deployment tasks using Jenkins
Berufserfahrung
- ca. 4 - 6 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- PyTorch
- Python
- C++
- RUST
- Git
- RNN
- Transformers
- VLM
- VLA
- LLM
Benefits
Mehr Urlaubstage
- 30 days of vacation
Attraktive Vergütung
- Overtime compensation
Sicherer Arbeitsplatz
- Secure, permanent employment relationship
Weiterbildungsangebote
- Internal development opportunities
- Internal and external training
- Coaching and certifications
Lockere Unternehmenskultur
- International work environment
- Inclusive work environment
Gemeinnützige Ausrichtung
- CSR activities
Moderne Technikausstattung
- State-of-the-art technology
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Senior ML Engineer(m/w/x)
Automated pipeline optimization and reinforcement learning for automotive sensor platforms. Ph.D. in computer science or machine learning required. 30 days vacation, overtime compensation.
Anforderungen
- Ph.D. in computer science, machine learning, or related field, or master degree with extensive experience
- Excellent analytical skills and mathematical background
- Professional experience in two specific areas
- Knowledge of deep neural networks and ML techniques
- Knowledge of reinforcement learning techniques
- Experience in time series prediction with RNN
- Knowledge of SOTA ML techniques and transformers
- Experience in generative, foundation, and language models
- Systematic, goal and outcome oriented working style
- Professional experience in PyTorch
- Professional skills in Python and C++
- Oral and written English skills
- Experience in datasets and data science methods
- Understanding of edge processing and RUST
- Experience in team software development and Git
- Proven track record of scientific publications
Aufgaben
- Develop and evaluate machine learning models using supervised, unsupervised, and reinforcement learning
- Conduct thorough model evaluation and validation using performance metrics
- Ensure model accuracy, reliability, and robustness
- Implement and optimize automated machine learning pipelines and frameworks
- Streamline model development, training, and deployment processes
- Automate feature engineering, model selection, and hyperparameter tuning
- Deploy and scale machine learning models on AWS, Azure, or Google Cloud
- Leverage cloud-based services for data storage, processing, and analysis
- Implement CI/CD pipelines for automated model deployment, testing, and monitoring
- Integrate AI/ML solutions into existing software development workflows
- Design AI/ML solutions following automotive product development standards
- Collaborate with cross-functional teams to align with product requirements
- Design and conduct A/B tests to evaluate real-world model impact
- Analyze test results to provide data-driven optimization recommendations
- Orchestrate ML workflows using Kubeflow Pipelines in Kubernetes environments
- Automate build, test, and deployment tasks using Jenkins
Berufserfahrung
- ca. 4 - 6 Jahre
Ausbildung
- Master-Abschluss
Sprachen
- Englisch – verhandlungssicher
Tools & Technologien
- PyTorch
- Python
- C++
- RUST
- Git
- RNN
- Transformers
- VLM
- VLA
- LLM
Benefits
Mehr Urlaubstage
- 30 days of vacation
Attraktive Vergütung
- Overtime compensation
Sicherer Arbeitsplatz
- Secure, permanent employment relationship
Weiterbildungsangebote
- Internal development opportunities
- Internal and external training
- Coaching and certifications
Lockere Unternehmenskultur
- International work environment
- Inclusive work environment
Gemeinnützige Ausrichtung
- CSR activities
Moderne Technikausstattung
- State-of-the-art technology
Gefällt dir diese Stelle?
BetaDein Career Agent findet täglich ähnliche Jobs für dich.
Über das Unternehmen
Aptiv
Branche
Automotive
Beschreibung
Das Unternehmen ist ein weltweit führender Automobilzulieferer mit einem Umsatz von über 20 Mrd. USD jährlich.
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