Computer Vision and Machine Learning Software Developer

5 days ago

Kota, Rajasthan, India beBeesoftware Full time US$ 1,00,000 - US$ 1,50,000

At the forefront of industrial automation, we're seeking a talented CV/ ML Software Engineer to join our team. This exciting role presents an exceptional opportunity to work on cutting-edge projects and contribute to shaping the future of our industry.

About the company is not part of this job description but may be found in other parts of the website or about page

**Key Responsibilities:**

  • We are looking for someone who can design and implement C++ software modules for on-device video capture, preprocessing, inference, and post-processing on Linux.
  • The ideal candidate should have experience with classical image processing pipelines (denoise, resize, color space, undistortion) and computer vision algorithms (keypoints, homography, optical flow, tracking).
  • This position requires building and optimizing distance estimation from monocular/stereo cameras using calibration, geometry, and depth-estimation networks.
  • We need someone who can integrate machine learning models (PyTorch/TensorFlow to ONNX/TensorRT/NNAPI/NPU runtimes) for driver monitoring system (DMS)/advanced driver-assistance system (ADAS) events: drowsiness, distraction/gaze, phone-usage, smoking, seat belt, etc.
  • Real-time targets (frames per second/latency/memory) on CPU/GPU/NPU using SIMD/NEON, multithreading, zero-copy buffers need to be met by the selected candidate.
  • Applicants should be able to write clean, testable C++, CMake builds, and Git-based workflows (branching, pull requests, code reviews, continuous integration).
  • Instrument logging/telemetry; debug with gdb/addr2line, sanitize and profile with perf/valgrind.
  • Candidates will collaborate with data/machine learning teams on dataset curation, labeling specifications, training/evaluation, and model handoff.

**Role Expectations:**

  • A minimum of 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 computer vision/machine learning 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.

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