Hybrid working, designing Edge AI and intelligent hardware systems for real-time applications.
I'm working with a deep tech company building next generation Edge AI and intelligent hardware platforms. They develop low power intelligent systems designed to run AI directly on hardware for real-time, high-performance applications across advanced electronics and embedded environments.
This is a high impact opportunity for an AI Engineer who wants to lead the deployment of AI systems for hardware platforms.
What they're looking for:
- Strong experience in Machine Learning, Edge AI, or Embedded AI
- Python with PyTorch, TensorFlow, or JAX
- Experience building, training, deploying, or optimising AI models
- Understanding of low power, low latency, or constrained hardware environments
- Interest in embedded systems, intelligent hardware, or FPGA accelerated platforms
- Experience working with sensor data, time series data, anomaly detection, or real time systems
- Ability to move from research into deployment
- Collaborative approach working across software, firmware, and hardware teams
- FPGA, embedded systems, ONNX/TensorRT, or hardware acceleration exposure (nice to have)
Why consider it:
- Cutting edge Edge AI and hardware projects
- High autonomy and real technical ownership
- Strong package including bonus and private healthcare
- Opportunity to build technology with real world impact