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 youll design and deploy intelligent vision systems powering next-generation 3D experiences spatial computing and immersive AR/MR/XR applications.

Youll 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

Required Skills:

Computer VisionDeep LearningPythonPyTorchTensorFlowOpenCV3D PerceptionImage ProcessingImage SegmentationObject Tracking3D ReconstructionMachine LearningModel deploymentEdge AICUDATensorRTLoRA