Computer Vision and Machine Learning Solutions Architect

3 days ago

Surat, Gujarat, India beBeeMachineLearning Full time ₹ 15,00,000 - ₹ 25,00,000
Expert Computer Vision and Machine Learning Engineer">

About the Role:

A highly skilled engineer is required to join our team, focusing on developing advanced computer vision and machine learning solutions for industrial automation. The ideal candidate will possess hands-on experience with modern C++ on Linux, strong Git and CMake skills, and a solid foundation in image processing and computer vision.

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Key Responsibilities:

  • Design and implement cutting-edge software modules for video capture, processing, inference, and post-processing on Linux.
  • Develop sophisticated image processing pipelines and computer vision algorithms, including keypoints, homography, optical flow, and tracking.
  • Built and optimized distance estimation from monocular and stereo cameras using calibration, geometry, and depth-estimation networks.
  • Integrated machine learning models for driver monitoring systems and advanced driver-assistance systems (ADAS), including drowsiness detection, distraction detection, and phone usage alerts.
  • Met real-time targets on CPU/GPU/NPU using SIMD, multithreading, and zero-copy buffers.
  • Written clean, testable C++ code, with experience in CMake builds and Git-based workflows.
  • Instrumented logging and telemetry; debugged using gdb and perf.
  • Collaborated with data and ML teams on dataset curation, labeling specs, training, evaluation, and model handoff.
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Requirements:

  • 2+ years of hands-on experience in modern C++ on Linux, with strong Git and CMake skills.
  • Solid image processing and computer vision foundations, including camera models, intrinsics, and distortion.
  • Practical experience integrating CV/ML models on device, with expertise in OpenCV and ONNX Runtime.
  • Experience building real-time pipelines for live video, optimizing for latency and memory.
  • Competence in multithreading, concurrency, and producer-consumer designs.
  • Knowledge of monocular depth estimation, stereo matching, or structure from motion for distance estimation.
  • Model training exposure, including augmentation, evaluation, and conversion to ONNX/TensorRT/NCNN.
  • Hardware acceleration, YOLO/RT DETR/Lightweight backbones on edge, and cross-compiling.
  • Familiarity with MQTT/IoT, message schemas, and over-the-air updates.
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What We Offer:

A dynamic work environment, opportunities for growth and professional development, and a competitive compensation package.

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