(Senior) MLOps Engineer (d/m/w)
Core
Build and maintain ML training and integration infrastructure for autonomous UAVs and defense/dual-use applications, bridging DevOps and Machine Learning Engineering.
Role type
Senior MLOps Engineer
Builds
MLOps platform, end-to-end autonomy stack, and production-ready ML components for autonomous systems
Domain
Aerospace & Defense, Autonomous Systems, Machine Learning
Deliverable
production ML models
Required skills
Python, Kubernetes, CI/CD, PyTorch, ONNX, MLflow, GitLab, KServe, Model Registry, Distributed Training, Model Optimization
Preferred skills
C++, TensorRT, Quantization, Hardware-in-the-Loop, Simulation Environments, Synthetic Data
Technologies
Kubernetes, MLflow, GitLab, Kubeflow, KServe, Artifact Registries, PyTorch, ONNX, TensorRT
Responsibilities
Design and build MLOps pipelines for training, evaluation, and deployment across multi-cloud and internal clusters; Ensure reproducibility and traceability across the model lifecycle; Integrate ML models into software and hardware-in-the-loop environments; Optimize models for target hardware and inference performance; Collaborate with ML, software, and system engineering teams to bridge the gap between development and production.
Seniority
Senior, hands-on IC
