SLAM & Computer Vision Engineer - YOLO

ABOUT US : Technosoft Engineering Solutions is building an AI-powered visual intelligence platform for the Indian construction industry. We bridge the gap between what is planned (BIM models, 2D drawings) and what is built on site, using real-time visual intelligence and spatial computing.THE ROLE : We are looking for a Computer Vision & AI Engineer to design and build scalable vision AI pipelines that process large volumes & variety. You will implement end-to-end AI pipeline : video preprocessing, model architecture (YOLO, SAM, segmentation models), training on construction datasets, inference optimization, and MLOps for continuous improvement.WHAT WE ARE LOOKING FOR : Computer Vision & Deep Learning (Core Requirement) : - Hands-on experience building object detection and segmentation models in production : YOLO, SAM (Segment Anything Model), or similar architectures- Strong fundamentals in CNNs, vision transformers, attention mechanisms, and multi-scale feature extraction- Practical experience with semantic segmentation and instance segmentation for complex, cluttered environments- Model training on custom datasets : data annotation pipelines, class imbalance handling, augmentation strategies- Transfer learning and fine-tuning : adapting pre-trained models to domain-specific tasks- Experience with 2D - to - 3D or video-to-BIM alignment is a strong plusLarge-Scale Video Processing & Inference Optimization (Core Requirement) : - Experience building scalable video processing pipelines handling TBs of data per month- Batch processing architecture : distributed inference across GPU clusters, queueing systems (RabbitMQ, Kafka, etc.), chunked video processing- Model optimization for production : quantization, pruning, ONNX Runtime, TensorRT- Frame sampling strategies for efficient video analysis (every Nth frame, keyframe extraction, motion-based sampling)- Experience with cloud-based GPU inference (AWS EC2 P3/P4, Lambda, SageMaker) and cost optimizationTraining Data & Domain-Specific Model Development (Core Requirement) : - Experience training models on noisy, real-world data : handling dust, shadows, occlusions, varying lighting conditions, motion blur- Building custom datasets : defining labeling guidelines, managing annotation teams, quality control- Multi-class classification with 50+ element classes across various construction segments- Defect detection modelling - cracks, rebar exposure, missing components, misalignments, incomplete work is strong plusHybrid 2D/3D AI & BIM Integration (Good to have) : - Experience working with BIM models (IFC files) or CAD drawings as reference for AI analysis- Spatial reasoning : matching detected elements in video frames to BIM element locations using coordinate transformations- Zone-based analysis : segmenting floor plans into zones, aggregating detection results per zone/floor- Progress quantification : computing completion percentages from detection outputs (e.g., "Floor 7 Finishes 40% complete")MLOps & Production AI Systems (Good to have) : - Model versioning, experiment tracking (MLflow, Weights & Biases, ClearML)- CI/CD for ML : automated retraining pipelines, A/B testing new models in production, monitoring model drift- Production monitoring : precision/recall tracking per class, confidence score distributions, detection latency, inference cost per video- Human-in-the-loop (HITL) workflows : flagging low-confidence predictions for manual review, feedback loops for continuous improvement- Experience with model explainability (Grad-CAM, SHAP) for debugging and trustProgramming Languages : - Python - expert level (PyTorch, TensorFlow, OpenCV, NumPy, Pandas)- Deep learning frameworks : PyTorch (preferred) or TensorFlow/Keras- Computer vision libraries : OpenCV, Albumentations, Pillow- GPU programming : CUDA basics, understanding GPU memory management- Familiar with video codecs (H.264, H.265), FFmpeg for video manipulationQUALIFICATIONS : - 5 - 10 years of professional software engineering experience- 3 - 5 years building production computer vision / deep learning system (ref:hirist.tech)