Our client is a well-funded Defence-Tech scale-up who are seeking a Senior Machine Learning Engineer to help scale its proprietary Large Acoustic Model (LAM) and edge-intelligence systems.
You will bridge classical signal processing with cutting-edge deep learning to turn non-speech audio into real-time intelligence for defense and security applications.
Core Responsibilities
- Model Training: Design and train deep learning models for acoustic event detection, classification, and localization.
- Signal Processing: Integrate advanced digital signal processing (DSP) with machine learning for robust audio feature extraction.
- Edge Optimization: Quantize, optimize, and deploy models onto ultra-low-power edge hardware for real-time inference.
- Collaboration: Work alongside hardware and physics teams to align software performance with embedded device constraints.
Key Requirements
- Proven experience as an ML Engineer focusing on audio, time-series, or signal processing.
- Strong proficiency in Python, PyTorch/TensorFlow, and modern ML frameworks.
- Practical background in acoustics and DSP.
- Experience with edge AI deployment (model quantization, pruning, and hardware constraints).
- Degree in Computer Science, Electrical Engineering, Signal Processing, or a related field.
