Machine Learning (ML) Engineer - Applied
Core
Developing and expanding an AutoML platform for embedded, edge, and IoT devices, focusing on model architecture selection, training, optimization, and validation.
Role type
Machine Learning Engineer (Edge AI & AutoML)
Builds
AutoML system for Edge AI, pipelines combining deep-learning and conventional algorithms, platform features for compute clusters and web applications.
Domain
Embedded AI, Edge AI, IoT, Computer Vision, Time-series, Audio, TinyML
Deliverable
production ML models
Required skills
Python, C/C++, TensorFlow, PyTorch, ONNX, scikit-learn, OpenCV, pandas, Linux development, model training and evaluation, edge device optimization
Preferred skills
PhD in CS/EE, AutoML experience, TinyML frameworks, multi-modal data handling
Technologies
TensorFlow, PyTorch, ONNX, scikit-learn, OpenCV, pandas, Linux
Responsibilities
Develop and enhance AutoML system for Edge AI, integrate new ML use-cases (vision, time-series, audio), optimize AI solutions for edge devices using TinyML, deploy ML algorithms on embedded targets, define abstractions for cloud and embedded components.
Seniority
Mid-Senior, hands-on IC
