About the Company : A Top Industrial Automation Company which is part of a Top Engineering Group
Job Description
- 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.
- Hit real time targets (FPS / latency / memory) on CPU / GPU / NPU using SIMD / NEON, multi threading, zero copy buffers.
- Write clean, testable C++, CMake builds, and Git based workflows (branching, PRs, code reviews, CI).
- Instrument logging / telemetry; debug with gdb / addr2line, sanitize and profile with perf / valgrind.
- Collaborate with data / ML teams on dataset curation, labeling specs, training / evaluation, and model hand-off.
Requirements
2+ years hands on in modern C++ on Linux, with strong Git and CMake.Solid image processing and computer‑vision foundations (camera models, intrinsics / extrinsics, distortion, PnP, epipolar geometry).Practical experience integrating CV / ML models on device (OpenCV + ONNX Runtime / TensorRT / NCNN / MediaPipe / NNAPI).Experience building real time pipelines for live video (GStreamer / FFmpeg, RTSP / RTMP, ring buffers), optimizing for latency & memory.Competence in multithreading / concurrency, lock free queues, and producer–consumer designs.Comfort with debugging & profiling on Linux targetsKnowledge of monocular depth estimation, stereo matching, or structure from motion for distance estimation.Model training exposure (PyTorch / TensorFlow) : augmentation, evaluation (precision / recall, ROC / PR), quantization / pruning, conversion to ONNX / TensorRT / NCNN.Hardware acceleration (GPU / VPU / NPU, Arm NEON / DSP), YOLO / RT DETR / Lightweight backbones on edge.Cross compiling, Yocto / Buildroot, containerized toolchains; unit tests (gtest), static analysis (clang tidy, cppcheck), sanitizers.Basic familiarity with MQTT / IoT, message schemas, and over the air updates.Please share your resumes at