
Visionary Software Engineer for Industrial Automation
2 weeks ago
About the Role
As a highly skilled Software Engineer in Computer Vision and Machine Learning, you will play a pivotal role in developing innovative solutions for industrial automation. You will be responsible for designing, implementing, and maintaining cutting-edge software modules for video capture, preprocessing, inference, and post-processing on Linux.
Key Responsibilities:
- Develop and maintain C++ software modules for on-device video capture, preprocessing, inference, and post-processing on Linux.
- Implement classical image processing pipelines (denoise, resize, color space, undistortion) and computer vision algorithms (keypoints, homography, optical flow, tracking).
- Build and optimize distance/spacing estimation from monocular/stereo camera(s) using calibration, geometry, and/or depth-estimation networks.
- Integrate machine learning models (PyTorch/TensorFlow → ONNX/TensorRT/NNAPI/NPU runtimes) for DMS/ADAS events: drowsiness, distraction/gaze, phone-usage, smoking, seat belt, etc.
- Meet real-time targets (FPS/latency/memory) on CPU/GPU/NPU using SIMD/NEON, multithreading, zero copy buffers.
- Write clean, testable C++, CMake builds, and Git-based workflows (branching, PRs, code reviews, CI).
- Instrument logging/telemetry; debug with gdb/addr2line, sanitize and profile with perf/valgrind.
- Collaborate with data/ML teams on dataset curation, labeling specs, training/evaluation, and model handoff.
Required Skills and Qualifications:
- 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.
- 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.
What We Offer:
As a member of our team, you will have the opportunity to work on cutting-edge projects, collaborate with experienced professionals, and develop your skills in computer vision and machine learning. We offer a dynamic and supportive work environment, opportunities for growth and development, and a competitive compensation package.
How to Apply:
If you are a motivated and talented individual with a passion for computer vision and machine learning, we encourage you to apply for this exciting opportunity. Please submit your resume, cover letter, and portfolio showcasing your relevant experience and skills.
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