· Own 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 CV 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 ML models (PyTorch/TensorFlow → ONNX/TensorRT/NNAPI/NPU runtimes) for DMS/ADAS events: drowsiness, distraction/gaze, phone-usage, smoking, seat belt, etc.
· Hit 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.
· Work with product & compliance to meet on road reliability, privacy, and regulatory expectations.
Requirements
· B.Tech/B.E. in CS/EE/ECE (or equivalent practical experience).
· 2–3 years in CV/ML or video-centric software roles. Hands on 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.
Requisites:
· 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.
Technical Competency:
· Languages: C++, Python
· CV/ML: OpenCV, ONNX Runtime/TensorRT/NCNN/MediaPipe; PyTorch/TensorFlow (for training/eval).
· Video: GStreamer/FFmpeg, V4L2, RTSP/RTMP.
· Build/DevOps: CMake, Git, gtest, clang-tidy, sanitizers; CI/CD (GitHub/GitLab/Bitbucket).
Skills Required
- B.Tech/B.E. in CS/EE/ECE or equivalent practical experience
- 2-3 years experience in computer vision/ML or video-centric software roles
- Proficient modern C++ development on Linux, strong Git and CMake skills
- Solid image processing and computer vision foundations (camera models, intrinsics/extrinsics, distortion, PnP, epipolar geometry)
- Practical experience integrating on-device CV/ML models (OpenCV, ONNX Runtime, TensorRT, NCNN, MediaPipe)
- Experience building real-time live-video pipelines (GStreamer/FFmpeg, V4L2, RTSP/RTMP, ring buffers) optimized for latency and memory
- Competence in multithreading/concurrency, lock-free queues, and producer-consumer designs
- Experience with debugging and profiling on Linux targets (gdb, perf, valgrind) and sanitizers
- Experience with driver monitoring or ADAS features, event logic and production thresholding
- Knowledge of monocular depth estimation, stereo matching, or structure-from-motion for distance estimation
- Model training exposure (PyTorch/TensorFlow): augmentation, evaluation, quantization/pruning, ONNX/TensorRT conversion
- Experience with hardware acceleration (GPU/VPU/NPU, Arm NEON/DSP) and edge detection backbones (YOLO, RT-DETR, lightweight models)
- Cross-compiling and embedded Linux build experience (Yocto/Buildroot), containerized toolchains, unit testing and static analysis
- Familiarity with MQTT/IoT message schemas and over-the-air update concepts
- Languages: C++ and Python
What We Do
Marketscope is a technology company specializing in the development and integration of Advanced Driver Assistance Systems (ADAS) and the scaling of production-grade AI/ML applications. The company focuses on AI platform engineering and product stacks, targeting strategic enterprise accounts and government sales, particularly within the Indian market, while expanding its reach into new international industries.
