Job
- Level
- Senior
- Job Field
- IT, Data, DevOps
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Munich
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop a scalable MLOps platform for autonomous driving, manage Kubernetes clusters on AWS EKS, and implement CI/CD pipelines for AI workflows.
Job Technologies
Your role in the team
- We are a cross-functional team driving the development and operation of a scalable MLOps platform for autonomous driving.
- Together, we enable innovative AI solutions by providing robust, cloud-native infrastructure for the entire machine learning lifecycle.
- You design, build, and manage Kubernetes clusters on AWS EKS with high security and scalability standards for autonomous driving AI/ML workloads.
- Furthermore, you provision and orchestrate large-scale GPU clusters for distributed AI/ML training and experimentation.
- Here, you implement and automate CI/CD pipelines for AI/ML workflows optimized for autonomous model lifecycle.
- Additionally, you develop and maintain infrastructure components such as experiment tracking, model registry, and artifact storage tailored to autonomous driving data.
- You monitor and optimize platform reliability, performance, and cost.
- Moreover, you implement resource scheduling, quota management, and cost control strategies within the MLOps environment.
- You collaborate closely with data scientists, AI/ML engineers, and cloud architects to ensure robust infrastructure for the entire AI/ML lifecycle.
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Our expectations of you
Education
- University degree in Computer Science, Data Science, AI, Mathematics, Physics or comparable qualifications.
Qualifications
- Profound expertise in Kubernetes, AWS EKS, and related cloud services.
- Umfassende Kenntnisse in der Infrastruktur für verteiltes Training und der Orchestrierung von GPU-Cluster in großem Maßstab.
- Advanced skills in Infrastructure as Code, especially Terraform and Helm.
- Very good written and spoken English skills; knowledge of German is an advantage.
Experience
- At least five years of professional experience in MLOps, DevOps, or Cloud Engineering with a focus on machine learning platforms.
- Strong proficiency in Python development, scripting and automation, with hands-on experience in CI/CD pipelines as well as monitoring and observability tools (e.g. ArgoCD, GitHub Actions, Prometheus, Grafana, OpenSearch/Kibana, CloudWatch).
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What we offer
- Challenging projects with which we are shaping the mobility of tomorrow together.
- Wide range of personal and professional development opportunities.
- Attractive, fair, and performance-related remuneration.
- High level of job security.
- Annual special payments such as vacation pay, Christmas bonus, and profit sharing.
- Flexible working hours including 6 weeks annual leave and overtime compensation.
- Discounted BMW & MINI conditions.
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Benefits
Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
BMW AG
Our world-leading premium automotive brands BMW, MINI, Rolls-Royce and our motorcycles, along with our comprehensive range of high-quality financial and mobility services make us a unique provider.
Description
- Company Type
- Established Company
- Working Model
- Hybrid, Onsite
- Industry
- Vehicle Manufacturing, Supplier, Industry, Production
Dev Reviews
by devworkplaces.com
Total
(2 Reviews)3.1
Career Growth
3.1Engineering
2.3Culture
3.1Workingconditions
4.1
Senior MLOps Engineer - Autonomous Driving Platform
- Location
- Munich
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
