CV/ ML Software Engineer

1 week ago

Tiruchi, 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 Group

Key Responsibilities

  • 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, 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 Expectations

  • 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.
  • 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 (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 bhawna@marketscope.in

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