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 rapid 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.

📌 AI/ML Engineer (Embedded / Edge Computing / Vision Systems) (Jaipur)
🏢 Triumph Motorcycles
📍 Jaipur