C++ Software Specialist

1 week ago

Allahabad, Uttar Pradesh, India beBeeSoftware Full time ₹ 2,00,00,000 - ₹ 2,50,00,000

About our organization, a top industrial automation firm which is part of a renowned engineering group.

Key Responsibilities
  • We are seeking a skilled professional to design and develop C++ software modules for on-device video capture, preprocessing, inference, and post-processing on Linux.
  • The ideal candidate will implement classical image processing pipelines and computer vision algorithms such as denoising, resizing, color space conversion, and undistortion.
  • This role involves building and optimizing distance estimation from monocular and stereo cameras using calibration, geometry, and depth-estimation networks.
  • The selected individual will integrate machine learning models for driver monitoring systems and advanced driver-assistance systems events.
  • Maintaining real-time targets on CPU, GPU, and NPU using SIMD, multithreading, and zero-copy buffers is crucial in this position.
  • Writing clean, testable C++ code and developing CMake builds and Git-based workflows are essential skills for this role.
  • Proficiency in logging and telemetry instrumentation, debugging with gdb and addr2line, and profiling with perf and valgrind is necessary.
Role Expectations
  • A minimum of 2+ years of experience in modern C++ on Linux, strong Git and CMake skills are required.
  • Solid foundations in image processing and computer vision are mandatory.
  • Practical experience integrating computer vision and machine learning models on device is necessary.
  • Experience building real-time pipelines for live video, optimizing for latency and memory is essential.
  • Competence in multithreading, concurrency, and producer-consumer designs is required.
  • Experience with driver monitoring or ADAS features is beneficial.
  • Knowledge of monocular depth estimation, stereo matching, or structure from motion is advantageous.
  • Model training exposure, augmentation, evaluation, quantization, and conversion to ONNX/TensorRT/NCNN is desirable.
  • Hardware acceleration, YOLO, RT DETR, and Lightweight backbones on edge are preferred.
  • Cross compiling, containerized toolchains, unit tests, static analysis, and sanitizers are highly valued.
  • Basic familiarity with MQTT/IoT and message schemas is a plus.

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