MLOps/ML Integration Engineer

We are currently seeking an experienced MLOps/ML Integration Engineer to drive our projects in this exciting field.

Responsibilities:

• Collaborate with ML researchers to package and deploy deep learning models and computer vision algorithms to edge and embedded systems.
• Adapt, optimize and integrate existing models for specific platforms.
• Set up and maintain monitoring, logging and versioning for ML training and deployment pipelines.

Must have:

• Knowledge of Python, C++ and Linux shell scripting.
• Experience deploying computer vision models on edge devices or embedded systems (e.g., NVIDIA Jetson, Intel-based systems, Raspberry Pi).
• Experience with model serving frameworks and inference formats (e.g., ONNX, TensorRT, OpenVINO)
• Understanding of algorithm profiling and optimization.

Nice to have:

• Experience with model optimization for the edge computational platforms (e.g. non-standard quantization).
• Understanding of core computer vision tasks (object detection, image classification, etc.).
• Familiarity with MLflow, DVC, or similar tools for experiment tracking and version control.
• Experience with GStreamer for developing real-time video streaming pipelines