CV/ ML Software Engineer

4 weeks ago


New Delhi, India A Top Industrial Automation Company which is part of a Top Engineering Group Full time

About the Company: A Top Industrial Automation Company which is part of a Top Engineering GroupKey ResponsibilitiesOwn 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, multithreading, 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 handoff.Role Expectations2+ years hands on inmodern C++on Linux, with strongGitandCMake . Solidimage processingandcomputer‑visionfoundations (camera models, intrinsics/extrinsics, distortion, PnP, epipolar geometry). Practical experience integratingCV/ML modelson device (OpenCV + ONNX Runtime/TensorRT/NCNN/MediaPipe/NNAPI). Experience buildingreal time pipelinesfor live video (GStreamer/FFmpeg, RTSP/RTMP, ring buffers), optimizing forlatency & memory . Competence inmultithreading/concurrency , lock free queues, and producer–consumer designs. Experience withdriver monitoringorADASfeatures; event logic and thresholding for production alerts. Knowledge of monocular depth estimation, stereo matching, or structure from motion fordistance estimation . Model training exposure ( PyTorch/TensorFlow ): augmentation, evaluation (precision/recall, ROC/PR), quantization/pruning, conversion to ONNX/TensorRT/NCNN. Hardware acceleration (GPU/VPU/NPU, ArmNEON /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 withMQTT/IoT , message schemas, and over the air updates.Please share your resumes at bhawna@marketscope.in


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