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
Solid Python and related libraries
Robust AI/ML basics, Image processing, Image compression, Model training
Robust 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.

📌 Ai/ml Engineer Embedded / Edge Computing / Vision Systems Jaipur
🏢 Triumph Motorcycles
📍 Jaipur