Vision Solution Architect
Computer Vision, VLMs & Multimodal GenAI Architecture
Experience Level: 8-12 years
Employment Type: Full time
Location: Pune, Chennai, Hyderabad, Kolkata, Delhi, Bangalore

About the Role
We are looking for a Vision Solution Architect to design and lead end-to-end computer vision and multimodal AI solutions — spanning classical vision models, CLIP-style embedding models, Vision-Language Models (VLMs), and Vision RAG architectures. The ideal candidate can architect solutions across cloud hyperscalers and edge deployments, guiding fine-tuning, integration, and productionization of vision and multimodal GenAI systems for real-world business use cases.

Key Responsibilities
• Architect end-to-end vision and multimodal GenAI solutions, from use-case discovery and model selection through deployment and monitoring.
• Design solutions leveraging CLIP-style embedding models, VLMs (e.g., LLaVA, Gemini Vision, GPT-4V/Claude Vision, Qwen-VL), and traditional CV models (detection, segmentation, OCR).




• Design and implement Vision RAG pipelines — multimodal embedding generation, vector indexing/retrieval, and grounding of VLM outputs against visual and textual knowledge bases.
• Lead fine-tuning and domain adaptation of vision and vision-language models (LoRA/QLoRA, adapter-based tuning, contrastive fine-tuning) for domain-specific accuracy.
• Architect solutions across hyperscaler vision/AI services — AWS (Rekognition, Bedrock multimodal models, SageMaker), GCP (Vertex AI Vision, Gemini multimodal APIs), and Azure (AI Vision, Azure AI Foundry) — selecting the right managed vs. self-hosted approach.
• Design edge deployment architectures for vision models on constrained devices (NVIDIA Jetson, edge TPUs, mobile/embedded accelerators), including model compression and quantization.
• Select and optimize model formats, runtimes, and accelerators (ONNX, TensorRT, OpenVINO, CoreML) for target hardware and latency/throughput requirements.
• Define evaluation f

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