Machine Vision Engineer

3 weeks ago


tamil nadu, India T&M Services Consulting Pvt Ltd Full time

Job Description: Machine Vision Engineer Department: Machine Vision / Computer Vision Location: Chennai Type: Full-time Experience : Mid senior to Senior (3–10+ years) Location: Sriperumbudur, Chennai Key Responsibilities Algorithm Development: Design, implement, and optimize computer vision and deep learning algorithms for object detection, segmentation, 3D reconstruction, OCR, anomaly detection, and pose estimation. End-to-End Pipeline Ownership: Develop and maintain robust vision pipelines, encompassing data ingestion, preprocessing, inference, post-processing, and system integration. Model Lifecycle Management: Train, fine-tune, evaluate, and deploy deep learning models (CNNs, Transformers, etc.) using frameworks like PyTorch, TensorFlow, or JAX. Data Strategy: Lead dataset curation, annotation, and augmentation efforts, including the use of synthetic data generation to improve model robustness. Testing & Validation: Conduct rigorous testing, benchmarking, and error analysis under real-world conditions to ensure system reliability and performance. Performance Optimization: Optimize models for edge deployment using techniques such as quantization, pruning, and leveraging inference engines like TensorRT, ONNX, or OpenVINO to meet strict latency and power constraints. Embedded Integration: Collaborate with embedded engineers to port and optimize vision software for various hardware platforms (SoCs, GPUs, NPUs). Research & Innovation: Stay current with the latest research in computer vision and machine learning, rapidly prototyping new techniques to enhance our capabilities. Software Engineering Best Practices: Write clean, documented, and maintainable code, and actively contribute to internal libraries, tools, and code reviews. Required Qualifications Bachelor’s/master’s in computer science, Electrical Engineering, Robotics, or a related field. 3+ years of hands-on industry experience in computer vision or machine learning (including relevant internships). Strong programming proficiency in Python and C++ . Deep, practical experience with at least one major deep learning framework (PyTorch is strongly preferred ). A proven track record of deploying real-time computer vision systems into a production environment. Solid foundation in classic computer vision (OpenCV, camera calibration, feature detection, multi-view geometry). Experience working with 2D/3D data formats, point clouds, and sensor fusion (e.g., camera with LiDAR/IMU). Preferred Skills & Experience Publications or significant contributions at top-tier conferences (CVPR, ICCV, ECCV, NeurIPS, ICRA, IROS). Experience with large-scale distributed model training. Familiarity with MLOps tools and practices (e.g., Docker, Kubernetes, MLflow, Weights & Biases). Domain experience in robotics, autonomous systems, medical imaging, or industrial quality inspection. Knowledge of safety-critical software standards (e.g., IEC 61508, ISO 26262). Strong mathematical background in linear algebra, probability, optimization, and 3D geometry.



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