Sr. AI Computer Vision Engineer-IT-Bengaluru-40 LPA

Profile: Sr. AI Computer Vision Engineer-IT-Bengaluru

Experience:

• 5+ years of experience in Computer Vision, Deep Learning, and AI
• Strong experience building production-grade AI systems
• Deep understanding of computer vision and deep learning algorithms
• Strong Python and software engineering fundamentals
• Experience with end-to-end ML training and deployment pipelines
• Hands-on expertise with PyTorch, TensorFlow, and OpenCV
• Experience optimizing models for edge deployment

About the role:

Senior AI Computer Vision Engineer with deep expertise in computer vision, deep learning, 3D perception, and production AI systems. This is a 100% hands-on individual contributor role where you’ll design and deploy intelligent vision systems powering next-generation 3D experiences, spatial computing, and immersive AR/MR/XR applications. 

You’ll work across computer vision, multimodal learning, edge AI deployment, 3D reconstruction, and ML infrastructure to build scalable, production-grade AI systems.

Roles:

1. Computer Vision & 3D Perception 

• Build advanced image understanding and scene analysis pipelines
• Develop 3D reconstruction and spatial understanding systems from multi-view inputs 
• Design depth estimation, pose estimation, and camera calibration solutions
• Implement object detection, segmentation, tracking, and feature extraction models 
• Build scene understanding and semantic mapping pipelines 
• Develop image enhancement, preprocessing, and intelligent data workflows
• Create real-time perception systems for AR/MR/XR applications
• Enable ML-driven visual analytics and spatial intelligence 

2. Deep Learning & AI Model Development 

• Design and optimize deep learning architectures for visual intelligence
• Train and fine-tune CNNs, transformers, MLLMs, and multimodal models
• Build perception, recognition, classification, and prediction systems
• Experiment with state-of-the-art AI approaches for visual computing
• Develop augmentation, evaluation, and continuous improvement pipelines
• Rapidly prototype using latest research and emerging frameworks 

3. Edge AI & Production Deployment 

• Build end-to-end ML pipelines including ingestion, preparation, training, and deployment 
• Deploy optimized models across edge environments and production systems
• Improve latency, throughput, and power efficiency for inference workloads
• Optimize models using TensorRT, CUDA, and hardware acceleration techniques 
• Design scalable deployment architectures 
• Implement monitoring, validation, and model lifecycle management

4. ML Infrastructure & System Engineering 

• Develop scalable AI services and modular deployment frameworks
• Build APIs and reusable AI components 
• Implement CI/CD pipelines for ML workloads 
• Containerize and orchestrate systems using modern infrastructure tooling
• Support annotation, validation, and production-quality operations
• Monitor model performance, drift, and reliability 

5. Research & Innovation 

• Stay updated with advances in AI, computer vision, and 3D perception
• Prototype solutions using latest multimodal and vision technologies
• Evaluate and integrate open-source frameworks into production
• Contribute to architecture decisions and technical strategy 
• Document learnings and share technical insights internally

Qualification:

• Experience in product visualization, advertising, or fashion content
• Familiarity with AI video pipelines and multi-frame consistency
• Knowledge of LoRA training, fine-tuning, or custom model workflows
• Understanding of branding and visual identity systems
• Exposure to 3D workflows or hybrid AI + 3D pipelines