SLAM & Computer Vision Engineer - YOLO (India)

SLAM & Computer Vision Engineer - YOLO (India)

19 Aug
|
Technosoft Engineering Projects
|
India

19 Aug

Technosoft Engineering Projects

India

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 plus

Large-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 optimization

Training 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 plus

Hybrid 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 trust

Programming 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 manipulation

QUALIFICATIONS :

- 5 - 10 years of qualified software engineering experience
- 3 - 5 years building production computer vision / deep learning system

📌 SLAM & Computer Vision Engineer - YOLO (India)
🏢 Technosoft Engineering Projects
📍 India

Reply to this offer

Impress this employer describing Your skills and abilities, fill out the form below and leave Your personal touch in the presentation letter.

Subscribe to this job alert:

Get the latest job offers by email for: slam & computer vision engineer - yolo (india) / india

Subscribe to this job alert:

Get the latest job offers by email for: slam & computer vision engineer - yolo (india) / india