ML Platform Engineer (m/f/d)

Agile Robots SE; München; Vor Ort; EUR 70.000 - 90.000; Vollzeit

Benefits dieser Stelle

Corporate Benefits Program

Modern office facilities

Collaborative work environment

Regular company events

Zusammenfassung

Agile Robots SE is seeking an ML Platform Engineer (m/f/d) to develop and operate the critical infrastructure for ML model deployment and training. You will design distributed training workflows, build ML environments, and maintain CI/CD pipelines, working closely with diverse teams. The role requires expertise in Python, cloud infrastructure, and experience with tools like Kubernetes and Docker.

Join a dynamic company focused on innovation, providing opportunities for professional growth through impactful projects and a supportive environment in Munich.

Qualifikationen

• Proven experience in building and operating ML or software infrastructure in production.
• Experience designing and operating distributed training systems.
• Hands-on experience with CI/CD pipelines for ML.

Aufgaben

• Design and scale distributed training workflows for large models.
• Build and maintain containerised ML environments.
• Develop and maintain CI/CD pipelines for machine learning systems.
• Implement experiment tracking and model versioning workflows.
• Set up monitoring systems to track model performance.
• Collaborate with research, data, and robotics teams.

Kenntnisse

Distributed training systems

CI/CD pipelines

Cloud infrastructure (AWS)

Python programming

Monitoring with Prometheus and Grafana

Experiment tracking tools (MLflow, Weights & Biases)

Ausbildung

Degree in Computer Science or related field

Tools

Docker

Kubernetes

Terraform

Jobbeschreibung

The AI Research Division of Agile Robots is looking for an ML Platform Engineer (m/f/d), who will build and operate the distributed training, deployment, and experimentation infrastructure that research, data, and robotics teams depend on to move models from prototype to production.

Your Responsibilities

• Training Infrastructure: Design and scale distributed training workflows for large models using tools such as PyTorch Distributed, DeepSpeed, and cluster schedulers like SLURM or Kubernetes.
• ML Platform: Build and maintain containerised ML environments that support reproducible experimentation and benchmarking.
• CI/CD Pipelines: Develop and maintain CI/CD pipelines for machine learning systems to enable reliable testing, training, and deployment of models.
• Lifecycle Management: Implement experiment tracking, model versioning, and reproducibility workflows using tools such as ClearML or Weights & Biases.
• Observability: Set up monitoring systems such as Prometheus and Grafana to track model performance and system health and detect drift in production.
• Cross-Team Collaboration: Work with research, data, and robotics teams to connect new models to robust production systems.
• Background and Experience: Degree in Computer Science, Software Engineering, or a related field, with professional experience building and operating ML or software infrastructure in production.
• Distributed Training: Experience designing and operating distributed training systems on Kubernetes and Docker, using PyTorch Distributed, DeepSpeed, and schedulers such as SLURM.
• CI/CD For ML: Experience building CI/CD pipelines that support reliable model testing, training, and deployment.
• Cloud Infrastructure: Experience operating ML workloads on cloud infrastructure, preferably AWS.
• Experiment Tracking: Hands-on experience with experiment tracking and model versioning using tools such as MLflow or Weights & Biases.
• Observability: Experience with monitoring and drift detection using tools such as Prometheus and Grafana.
• Software Engineering: Python and system design skills, with experience building and operating ML systems beyond the prototype stage.

Beneficial Skills

• Multimodal Systems: Experience with large-scale or multimodal ML systems such as vision-language-action models.
• Infrastructure As Code: Familiarity with infrastructure-as-code tools such as Terraform.
• ML Orchestration: Experience with ML pipeline and orchestration tools.
• Distributed Compute: Exposure to high-performance or distributed compute environments.

What we offer

• Dynamic high-tech company combined with financial soundness and world class investors.
• Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment.
• Lots of development opportunities in the context of our continued growth.
• Challenging tasks and impactful projects alongside experts that enable professional and personal growth.
• Corporate Benefits Program that covers health, mobility and learning with 100 € net per month.
• Modern office facilites with a rooftop terrace overlooking Munich, free drinks & fruits, and regular company events contribute to a good working environment.

We are proud of our diversity and welcome your application regardless of gender and sexual identity, nationality, ethnicity, religion, age, or disability.