Senior ML Platform Engineer (m/f/d)

Salary: 44.000 - 81.000 € per year

Requirements:

Degree in Computer Science, Artificial Intelligence, Data Engineering, or a related technical discipline.

Strong software engineering skills in Python, with experience building reliable, maintainable software and automated workflows for data-intensive machine learning systems.

Several years of hands-on experience building production ML platforms, MLOps systems, or large-scale data and training pipelines.

Solid knowledge of machine learning fundamentals and hands-on experience training and evaluating ML models.

Deep understanding of the ML lifecycle, including dataset preparation, distributed training, experiment management, model validation, and reproducibility.

Experience with cloud platforms and containerized infrastructure using Docker and Kubernetes.

Experience with workflow orchestration, experiment tracking, and model or artifact management technologies such as Argo Workflows, Kubeflow, Metaflow, Airflow, MLflow, or comparable solutions.

Practical experience with large datasets, object and shared storage, data formats, partitioning or sharding strategies, and high-throughput data loading.

Familiarity with CI/CD, infrastructure as code, monitoring, logging, access control, and operating reliable production systems.

Confident English communication skills and the ability to collaborate effectively across research, product, and infrastructure teams.

High self-motivation and technical ownership from architecture through operation.

Responsibilities:

Design, implement, and operate scalable ML and data pipelines covering ingestion, dataset creation, training, and model validation.

Build a reliable ML platform for reproducible experimentation and training across local, on-premises, and cloud GPU infrastructure.

Develop efficient systems for large-scale multimodal datasets, including imagery, LiDAR, odometry, ground truth, and simulation data.

Establish dataset and model versioning, metadata management, quality checks, and traceability from raw sensor data to validated model artifacts.

Build and optimize distributed training workflows, job scheduling, GPU resource allocation, caching, and high-throughput data access.

Develop AI-powered tools for internal data engineering, including semantic data search, metadata enrichment, automatic annotation, and quality assessment using foundation or multimodal models.

Improve platform reliability, observability, security, cost efficiency, and developer experience.

Collaborate with ML, data, and engineering teams to translate their technical needs into scalable platform capabilities.

Mentor engineers, contribute to architectural decisions, and establish engineering standards for production-grade ML systems.

Technologies:

AI

Airflow

CI/CD

Cloud

Docker

GIS

Support

Kubeflow

Kubernetes

Machine Learning

MLflow

MLOps

Python

Robotics

Security

Hardware

Mobile

Model Training

More:

We are hiring a Senior Machine Learning Platform Engineer to build the platform that turns large-scale UxV and sensor data into validated, reproducible machine learning models. Your work will provide the foundations our AI teams use to develop autonomy and perception capabilities and contribute to our next generation of autonomous UxV solutions. We develop advanced autonomous systems for defense and security operations across multiple domains, powered by integrated software and AI, and build smart aerial, ground, and naval robotics for security, defense, public safety, commercial, industrial, and GIS sectors. We value combined technical expertise and customer focus, ambition, bold thinking, and technological excellence, and support individual and professional growth. Our benefits include a company pension scheme, trust-based flexible working hours, one flexible remote-work day per week, subsidized EGYM Wellpass membership, bike leasing, corporate discounts, employee events, a sponsored daily lunch budget, and a shuttle from Laim in Munich. We value and actively promote diversity, and strive to create an inclusive workplace where every voice is heard and employees can reach their full potential.

last updated 42 week of 2026