Research Engineer - ADAS (ID 1281)

About the role

Integrate ML models (PyTorch/TensorFlow → ONNX/TensorRT/NNAPI/NPU runtimes) for DMS/ADAS events: drowsiness, distraction/gaze, phone-usage, smoking, seat belt, etc. Hit real time targets (FPS/latency/memory) on CPU/GPU/NPU using SIMD/NEON, multithreading, zero copy buffers. Write clean, testable C++, CMake builds, and Git based workflows (branching, PRs, code reviews, CI).

What you'll do

• Own C++ software modules for on device video capture, preprocessing, inference, and post processing on Linux
• Implement classical image processing pipelines (denoise, resize, color space, undistortion) and CV algorithms (keypoints, homography, optical flow, tracking)
• Build and optimize distance/spacing estimation from monocular/stereo camera(s) using calibration, geometry, and/or depth-estimation networks
• Integrate ML models (PyTorch/TensorFlow → ONNX/TensorRT/NNAPI/NPU runtimes) for DMS/ADAS events: drowsiness, distraction/gaze, phone-usage, smoking, seat belt, etc
• Write clean, testable C++, CMake builds, and Git based workflows (branching, PRs, code reviews, CI)

What you need

• 2–3 yrs of experience
• Research
• C++
• IoT
• Python
• Computer vision
• Machine learning
• B.Tech or B.E.

Good to have

• Git
• Linux
• PyTorch
• TensorFlow
• CI/CD