Cv/ ml software engineer

3 weeks ago

Erode, Tamil Nadu, 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 (Py Torch/Tensor Flow → ONNX/Tensor RT/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 in modern C++ on Linux, with strong Git and CMake.Solid image processing and computer‐vision foundations (camera models, intrinsics/extrinsics, distortion, Pn P, epipolar geometry).Practical experience integrating CV/ML models on device (Open CV + ONNX Runtime/Tensor RT/NCNN/Media Pipe/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.Experience with driver monitoring or ADAS features; event logic and thresholding for production alerts.Knowledge of monocular depth estimation, stereo matching, or structure from motion for distance estimation.Model training exposure (Py Torch/Tensor Flow): augmentation, evaluation (precision/recall, ROC/PR), quantization/pruning, conversion to ONNX/Tensor RT/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/Io T, message schemas, and over the air updates.Please share your resumes at

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