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Senior MLOps Engineer - Autonomous Driving Platform(m/w/x)
Building and managing cloud-native platform infrastructure for autonomous driving, orchestrating large-scale GPU clusters on AWS EKS. Five years MLOps/DevOps/Cloud Engineering experience with machine learning platforms and Kubernetes/AWS EKS expertise required. Six weeks annual leave, flexible working hours, overtime compensation.
Requirements
- University degree in Computer Science, Data Science, AI, Mathematics, Physics, or comparable qualifications
- At least five years professional experience in MLOps, DevOps, or Cloud Engineering with machine learning platforms focus
- Proficient expertise in Kubernetes, AWS EKS, and related cloud services
- Comprehensive knowledge of distributed training infrastructure and large-scale GPU cluster orchestration
- Advanced skills in Infrastructure as Code, especially Terraform and Helm
- Strong proficiency in Python development, scripting, automation, CI/CD pipelines, monitoring, and observability tools
- Very good written and spoken English skills
- Advantageous knowledge of German
Tasks
- Design, build, and manage Kubernetes clusters on AWS EKS
- Provision and orchestrate large-scale GPU clusters for AI/ML
- Implement and automate CI/CD pipelines for AI/ML workflows
- Develop and maintain experiment tracking for autonomous driving
- Develop and maintain model registries for autonomous driving
- Develop and maintain artifact storage for autonomous driving
- Monitor and optimize platform reliability
- Monitor and optimize platform performance
- Monitor and optimize platform cost
- Implement resource scheduling in MLOps
- Implement quota management in MLOps
- Implement cost control in MLOps
- Collaborate with data scientists, AI/ML engineers, and cloud architects
Work Experience
- 5 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
- German – Basic
Tools & Technologies
- Kubernetes
- AWS EKS
- Terraform
- Helm
- Python
- ArgoCD
- GitHub Actions
- Prometheus
- Grafana
- OpenSearch
- Kibana
- CloudWatch
Benefits
Flexible Working
- Flexible working hours
More Vacation Days
- 6 weeks annual leave
Competitive Pay
- Overtime compensation
Bonuses & Incentives
- Christmas bonus
- Profit sharing
Learning & Development
- Personal development opportunities
- Professional development opportunities
Job Security
- Job security
Corporate Discounts
- Discounted BMW & MINI conditions
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Senior MLOps Engineer - Autonomous Driving Platform(m/w/x)
Building and managing cloud-native platform infrastructure for autonomous driving, orchestrating large-scale GPU clusters on AWS EKS. Five years MLOps/DevOps/Cloud Engineering experience with machine learning platforms and Kubernetes/AWS EKS expertise required. Six weeks annual leave, flexible working hours, overtime compensation.
Requirements
- University degree in Computer Science, Data Science, AI, Mathematics, Physics, or comparable qualifications
- At least five years professional experience in MLOps, DevOps, or Cloud Engineering with machine learning platforms focus
- Proficient expertise in Kubernetes, AWS EKS, and related cloud services
- Comprehensive knowledge of distributed training infrastructure and large-scale GPU cluster orchestration
- Advanced skills in Infrastructure as Code, especially Terraform and Helm
- Strong proficiency in Python development, scripting, automation, CI/CD pipelines, monitoring, and observability tools
- Very good written and spoken English skills
- Advantageous knowledge of German
Tasks
- Design, build, and manage Kubernetes clusters on AWS EKS
- Provision and orchestrate large-scale GPU clusters for AI/ML
- Implement and automate CI/CD pipelines for AI/ML workflows
- Develop and maintain experiment tracking for autonomous driving
- Develop and maintain model registries for autonomous driving
- Develop and maintain artifact storage for autonomous driving
- Monitor and optimize platform reliability
- Monitor and optimize platform performance
- Monitor and optimize platform cost
- Implement resource scheduling in MLOps
- Implement quota management in MLOps
- Implement cost control in MLOps
- Collaborate with data scientists, AI/ML engineers, and cloud architects
Work Experience
- 5 years
Education
- Bachelor's degree
Languages
- English – Business Fluent
- German – Basic
Tools & Technologies
- Kubernetes
- AWS EKS
- Terraform
- Helm
- Python
- ArgoCD
- GitHub Actions
- Prometheus
- Grafana
- OpenSearch
- Kibana
- CloudWatch
Benefits
Flexible Working
- Flexible working hours
More Vacation Days
- 6 weeks annual leave
Competitive Pay
- Overtime compensation
Bonuses & Incentives
- Christmas bonus
- Profit sharing
Learning & Development
- Personal development opportunities
- Professional development opportunities
Job Security
- Job security
Corporate Discounts
- Discounted BMW & MINI conditions
About the Company
BMW Group
Industry
Automotive
Description
Das Unternehmen bietet spannende Praktika im Bereich Markenerlebnis und Eventmanagement und legt großen Wert auf Gleichbehandlung und Chancengleichheit.
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