C++ Software Developer

2 weeks ago

Palakkad, Kerala, India beBeeSoftwareEngineer Full time ₹ 1,20,00,000 - ₹ 2,50,00,000
Job Title: Software Engineer

We are seeking a skilled software engineer to develop and optimize C++ software modules for on-device video capture, preprocessing, inference, and post-processing on Linux.

This role involves implementing classical image processing pipelines and computer vision algorithms to enable advanced features in our products.

Responsibilities include:

  • Implementing image processing pipelines (denoise, resize, color space, undistortion) and computer vision algorithms (keypoints, homography, optical flow, tracking)
  • Building and optimizing distance/spacing estimation from monocular/stereo camera(s) using calibration, geometry, and/or depth-estimation networks
  • Integrating machine learning models (PyTorch/TensorFlow → ONNX/TensorRT/NNAPI/NPU runtimes) for DMS/ADAS events: drowsiness, distraction/gaze, phone-usage, smoking, seat belt, etc.
  • Collaborating with data/ML teams on dataset curation, labeling specs, training/evaluation, and model hand-off
Requirements

The ideal candidate should have:

  • 2+ years hands-on experience 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 targets
  • 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

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