Embedded Machine Learning Engineer (AI/ML)
Tasks
- Build datasets and model architectures
- Co design ML architectures for constrained embedded hardware
- Collaborate cross functionally to validate ML enabled innovations
- Establish benchmarks evaluation metrics pass fail criteria
- Explore ML augmented signal processing anomaly detection adaptive control
- Integrate ML inference with silicon firmware and systems
- Lead rapid prototyping of edge intelligence ML models
- Mentor engineers on ML model lifecycle
- Optimize model performance efficiency interpretability
- Scout external IP academic work and startups
Perks/Benefits
- N/A
Skills/Tech-stack
Anomaly Detection | Attention Mechanisms | Bare Metal | C plus plus | C# | Convolutional Neural Networks | CoreML | Deep learning | Edge Impulse | Embedded SoCs | Embedded Systems | GRU | Generative Models | Glow | Knowledge Distillation | LSTM | Machine Learning | Microcontrollers | Mixed Precision | Mixed-precision training | Model Compression | Neural Networks | ONNX Runtime | Pruning | Python | Quantization | RTOS | Recurrent Neural Networks | Reinforcement Learning | Representation Learning | Sequence Modeling | Sequence to sequence | Sequence-to-Sequence Modeling | TVM | TensorFlow Lite | TensorRT | Transformers
Education
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