Senior MLOps Engineer - Autonomous Driving Platform (f/m/x)

WER NEU DENKT, KANN AUTOS DAS DENKEN BEIBRINGEN.

TEILE DEINE LEIDENSCHAFT.

Um die Zukunft der Mobilität zu revolutionieren, müssen wir heute schon Maßstäbe setzen. Expert:innen aus dem Bereich Künstliche Intelligenz finden bei uns ideale Voraussetzungen dafür. Sie können ihre neu entwickelten Algorithmen direkt an den neuesten Fahrzeugen auf der Straße testen. Als visionäre Denker und kreative Entwickler:innen haben sie zudem persönliche Forschungsfreiheit und profitieren gleichzeitig von umfangreicher Unterstützung. Gemeinsam in Expertenteams und weltweit über Kompetenzzentren vernetzt, definieren unsere AI-Spezialist:innen immer aufs Neue die Grenzen des Möglichen.

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.

What awaits you?

• 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 driving 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.

 

What should you bring along?

• University degree in Computer Science, Data Science, AI, Mathematics, Physics or comparable qualifications.
• At least five years of professional experience in MLOps, DevOps, or Cloud Engineering with a focus on machine learning platforms.
• Profound 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 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).
• Very good written and spoken English skills; knowledge of German is an advantage.

Would you like to shape the future of autonomous driving by building scalable MLOps platforms for innovative AI solutions?  Apply now!

Find out more about Artificial Intelligence at the BMW Group here.

Note: Please apply exclusively online via our career portal. Applications via other channels (esp. e-mail) cannot be considered.

What do 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.
• Many other benefits at bmw.jobs/benefits

 

Start date: from now on

Type of employment:  unlimited
Working hours: full time

If you apply, the next stages of the recruiting process include online testing and then an interview with the hiring manager (either virtual or in person). 

 

You can find helpful tips on your application and the application process here.

At the BMW Group, we place great importance on equal treatment and equal opportunities. Our recruiting decisions are based on the personality, experience, and skills of the applicants.

Learn more here.