REPLACI

Lead Computer Vision Engineer

New Delhi, DL, IN

4 days ago
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Summary

About the Role

We are seeking a highly skilled Lead Computer Vision & Gen AI Engineer with 5 years of experience in designing and implementing diffusion models for furniture replacement in images and achieving ultra-realistic re-rendering. If you thrive on solving challenging AI problems and are passionate about creating innovative solutions in the field of computer vision and image generation, join us to redefine the future of virtual furniture visualization!


Position: Lead Computer Vision Engineer

Experience: 5 years

Employment Type: Full-Time

Location: Gurgaon, India



Key Responsibilities

• Design, develop, and optimize by fine-tuning diffusion models tailored for furniture detection,

replacement, placement in images, and ultra-realistic rendering.

• Create ultra-realistic image re-rendering pipelines for seamless integration of furniture in

diverse environments.

• Collaborate with product and design teams to understand requirements and deliver impactful

AI-powered solutions.

• Research and implement state-of-the-art generative AI techniques for photorealistic image

synthesis.

• Train, fine-tune, and deploy models, ensuring high accuracy and performance on large-scale

datasets.

• Develop scalable APIs and systems to integrate model capabilities into production workflows

by working closely with the DevOps Engineer.

Requirements

Experience:

• 3-4 years of experience in Generative AI with a focus on diffusion models.

• Demonstrable experience in furniture or object replacement and re-rendering using

generative models.

Skills:

• Strong proficiency in frameworks like PyTorch.

• Expertise in fine-tuning diffusion models (e.g., Stable Diffusion, Denoising Diffusion

Probabilistic Models).

• Expertise in distributed training using CUDA.

• Solid knowledge of GANs, NeRF, or other generative models for realistic image synthesis.

• Familiarity with 3D rendering pipelines, textures, and lighting models.

• Proficiency in creating and working with large datasets and optimizing model performance.

Soft Skills:

• Strong analytical and problem-solving skills.

• Excellent communication and ability to explain complex ideas and model architectures

clearly.

• A proactive and collaborative mindset for teamwork.



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