Advanced Machine Learning Software Developer

2 days ago

Kolkata, West Bengal, India beBeeSoftware Full time ₹ 1,80,00,000 - ₹ 2,40,00,000
Job Opportunity

We are seeking an accomplished software developer to join our team as a Machine Learning Software Engineer.

As a Machine Learning Software Engineer, you will be responsible for designing and developing cutting-edge software modules for video capture, preprocessing, inference, and post-processing on Linux.

Key responsibilities include implementing image processing pipelines and computer vision algorithms, including denoising, resizing, color space conversion, undistortion, keypoint detection, homography estimation, optical flow calculation, and object tracking.

You will also develop distance and spacing estimation capabilities using monocular and stereo camera configurations, along with calibration, geometry, and depth-estimation networks.

In addition, you will integrate machine learning models (PyTorch/TensorFlow to ONNX/TensorRT/NNAPI/NPU runtimes) for driver monitoring systems (DMS) and advanced driver-assistance systems (ADAS) events, such as drowsiness, distraction, gaze tracking, phone usage, smoking, and seat belt reminders.

Maintain real-time performance targets (FPS, latency, memory) on CPU, GPU, and NPU hardware using SIMD, NEON, multithreading, and zero-copy buffers.

Write clean, testable C++ code, implement CMake builds, and manage Git-based workflows, including branching, pull requests, code reviews, and continuous integration.

Instrument logging and telemetry, debug using gdb and addr2line, sanitize and profile using perf and valgrind.

Collaborate with data science and machine learning teams on dataset curation, labeling specifications, training, evaluation, and model deployment.

Required Skills and Qualifications
  • Minimum 2 years of hands-on experience in modern C++ on Linux, with strong Git and CMake skills.
  • Solid foundations in image processing and computer vision, including camera models, intrinsics, extrinsics, distortion, PnP, epipolar geometry, and other related concepts.
  • Practical experience integrating computer vision and machine learning models on device, using OpenCV and ONNX Runtime, TensorRT, NCNN, MediaPipe, and NNAPI.
  • Experience building real-time pipelines for live video processing, optimizing for latency and memory using GStreamer, FFmpeg, RTSP, RTMP, and ring buffers.
  • 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.
  • Exposure to model training (PyTorch/TensorFlow): data augmentation, evaluation (precision, recall, ROC, PR), quantization, pruning, and conversion to ONNX, TensorRT, NCNN.
  • Hardware acceleration (GPU, VPU, NPU, Arm NEON, DSP), YOLO, RT DETR, Lightweight backbones on edge devices.
  • 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.
Benefits
  • Develop cutting-edge technology in the field of machine learning.
  • Work with experienced professionals in a collaborative environment.
  • Participate in the development of innovative projects that shape the future of AI.
Others

This is an exciting opportunity to grow professionally while contributing to meaningful work. We value innovation and creativity, so if you're passionate about machine learning and have a talent for problem-solving, we'd love to hear from you.

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