Job
- Level
- Senior
- Job Field
- IT, Data, DevOps
- Employment Type
- Full Time
- Contract Type
- Permanent employment
- Location
- Gilching
- Working Model
- Hybrid, Onsite
Job Summary
In this role, you will develop automated, Kubernetes-based platforms for machine learning, enhance ML workflows, and design robust cloud infrastructures in a global environment.
Job Technologies
Your role in the team
- As a Platform Engineer - Cloud & ML Platform (m/f/d), you will be a key contributor to the cloud-native infrastructure that powers our AI and autonomy development at global scale.
- You will design, deploy, operate, and continuously improve Kubernetes-based platforms that enable our teams to train, evaluate, deploy, and monitor machine learning workloads reliably across regions, clouds, and compute environments.
- You will work closely with AI engineers, data engineers, software teams, security, IT, and product stakeholders to provide robust, automated, and developer-friendly infrastructure for large-scale ML workloads.
- Your work will directly support our mission to push the boundaries of autonomous systems through cutting-edge software, edge computing, and real-time AI-powered data processing.
- Design, deploy, operate, and continuously improve Kubernetes-based platforms for machine learning and data-intensive workloads.
- Build and maintain globally distributed Kubernetes clusters with a strong focus on reliability, scalability, security, and observability.
- Own the lifecycle management of ML platform components, including Kubeflow, Metaflow, workflow orchestration, experiment tracking, and related MLOps tooling.
- Enable AI and data teams to run scalable training, inference, evaluation, and data processing pipelines across heterogeneous compute environments.
- Develop infrastructure-as-code, automation, and GitOps workflows to ensure reproducible, auditable, and efficient platform operations.
- Manage GPU-enabled workloads, scheduling, storage, networking, secrets, access control, and cost-aware resource utilization.
- Improve platform resilience through monitoring, alerting, incident response, backup strategies, disaster recovery, and capacity planning.
- Collaborate with AI, software, DevOps, security, and IT teams to define platform standards, best practices, and deployment patterns.
- Support hybrid and multi-cloud infrastructure scenarios, including on-premise, private cloud, and public cloud environments.
- Evaluate and integrate cloud providers and infrastructure technologies, including Azure, AWS, Telekom Cloud, or comparable platforms.
- Continuously improve developer experience for ML engineers through self-service tooling, documentation, templates, and platform abstractions.
- Help bring AI capabilities from prototype to production by providing a reliable, scalable, and secure ML infrastructure foundation.
This text has been machine translated. Show original
Our expectations of you
Qualifications
- Strong hands-on expertise with Kubernetes in production environments, including cluster operations, networking, storage, security, scaling, upgrades, and troubleshooting.
- Solid understanding of MLOps workflows, including training pipelines, model lifecycle management, artifact handling, experiment tracking, reproducibility, and deployment automation.
- Gutes Verständnis von cloud-native Observability, einschließlich Metriken, Logs, Traces, Alerting, Dashboards und SLO-gesteuerten Operationen.
- Vertrautheit mit Cloud-Plattformen wie Azure, AWS, Telekom Cloud, GCP, OpenStack oder vergleichbaren Private/Hybrid-Cloud-Umgebungen.
- Strong scripting or programming skills in Python, Go, Bash, or a comparable language.
- Ability to analyze complex infrastructure issues, drive root-cause analysis, and implement robust long-term solutions.
- Structured, analytical mindset with a hands-on attitude and a strong sense of ownership.
- Strong communication skills and the ability to work with globally distributed engineering teams.
- Communication in English is a matter of course for you.
Experience
- Proven experience deploying and maintaining globally distributed, large-scale clusters for production or mission-critical workloads.
- Strong experience with Kubeflow and Metaflow in production or production-like ML platform environments.
- Experience operating GPU-enabled Kubernetes environments and supporting high-performance machine learning workloads.
- Strong infrastructure-as-code experience using tools such as Terraform, Helm, Kustomize, Argo CD, Flux, Crossplane, Ansible, or comparable technologies.
- Experience with containerization, CI/CD, GitOps, secrets management, identity and access control, and secure platform operations.
This text has been machine translated. Show original
What we offer
- Company pension scheme: We support you so that you can already make provisions for later.
- Flexible working hours: With trust-based working hours, you are not only responsible for your working hours, but also for your work-life balance.
- Mobile Work: If things get a little busy in the office, you have the option to work remotely one flexible day per week to create the right balance.
- Stay active: With EGYM Wellpass, you get access to thousands of fitness and sports facilities - and of course, we subsidize the membership.
- Bike leasing: We support you in staying environmentally mobile and healthy.
- Corporate Benefits: Your opportunity for attractive offers and discounts from well-known suppliers and brands, e.g., Adidas, Apple, Expedia.
- Employee events: We not only want to grow together, but also celebrate our successes together.
- Lunch Card: Be powerful with delicious energy, daily lunch budget is sponsored.
- Company Shuttle: Enjoy our convenient shuttle service that picks you up from Pasing in Munich and brings you to our location, with return trips at the end of the workday.
This text has been machine translated. Show original
Benefits
Work-Life-Integration
Topics that you deal with on the job
Job Locations
This is your employer
Quantum-systems Gmbh
Quantum-Systems GmbH began focusing on the development and production of autonomous transition aircraft for civilian purposes in January 2015. This was a smart move that has positioned the company as a leader in this growing industry. Autonomous transition aircraft are an important part of the future of aviation, and Quantum-Systems GmbH is at the forefront of this exciting new technology.
Description
- Company Size
- 50-249 Employees
- Language
- English
- Company Type
- Established Company
- Working Model
- Full Remote, Hybrid, Onsite
- Industry
- Industry, Production, Aviation, Space Travel
Senior Platform Engineer - Cloud & ML Platform
- Location
- Gilching
- Working Model
- Hybrid, Onsite
- Diversity
- Open for all genders
