AI/ML Engineer (Embedded / Edge Computing / Vision Systems)

Key Responsibilities

• Develop and optimise AI/ML models for embedded deployment
• Work with frameworks: TensorFlow Lite / ONNX / PyTorch
• Optimise for CPU / GPU / NPU acceleration
• Handle Image processing, sensor data pipelines
• Integrate and optimize AI/ML inference into embedded edge
• Collaborate with firmware & Linux teams for integration
• Analyse and optimize Models for accuracy and performance
• Collaborate with hardware teams for board bring-up

Key Skills

• Strong Python and related libraries
• Strong AI/ML basics, Image processing, Image compression, Model training
• Strong experience with Model optimisation, Accuracy and its performance on edge system
• Experience with: Edge hardware (MPU/MCU/NPU etc.)
• Image recognition, Image processing, Object Detection
• Knowledge of using HW acceleration techniques (NPU, AI, DSP)
• Integrate AI/ML model in embedded system and optimization
• Experience Developing, Building, Validating, deploying and optimizing neuralnetwork models for embedded targets (TensorFlow Lite, ONNX Runtime).
• Interface AI toolchains
• Basic Understanding of embedded C programming, Linux, RTOS Concept
• Support scenario testing for vibration, noise, variable lighting, weather, and fast motion typical of 2wheelers functional and performance validation.
• Cross Function Collaboration (Embedded, MATLAB, HW, Testing team)
• Unit test, Integration Test, Function test
• Adhere to automotive development standards (MISRA, ASPICE) as required.

To undertake and assist with duties as required by your manager.