As a Senior Machine Learning Platform Engineer (m/f/d), you will design and build the platform that turns large-scale UxV and sensor data into validated, reproducible machine learning models.
You will own and improve the end-to-end ML lifecycle—from data processing, selection, and annotation through distributed model training, experiment tracking and validation.
Your work will enable ML engineers to develop autonomy and perception capabilities efficiently, reliably, and at scale.
Beyond conventional platform engineering, you will also apply modern AI models to our internal data workflows.
This may include semantic dataset search, automated metadata generation, data curation, and auto-labeling using foundation and multimodal models.
By creating the foundations on which our AI teams build and validate models, you will directly contribute to Quantum Systems’ next generation of autonomous UxV solutions.
What is your Day to Day Mission: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.
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.
Improve platform reliability, observability, security, cost efficiency, and developer experience.