Lead Computer vision engineer

3 - 7 years

0 Lacs

Posted:2 weeks ago| Platform: Shine logo

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Work Mode

On-site

Job Type

Full Time

Job Description

This role is for one of Weekday's clients. You will be working as a Lead Computer Vision & Gen AI Engineer based in Gurugram on a full-time basis. With a minimum of 5 years of experience, you will be responsible for designing and implementing diffusion models for furniture replacement in images and achieving ultra-realistic re-rendering. If you enjoy tackling complex AI challenges and are enthusiastic about developing innovative solutions in computer vision and image generation, this is the opportunity to redefine the future of virtual furniture visualization. Your main responsibilities will include designing, developing, and optimizing diffusion models tailored for furniture detection, replacement, and placement in images, as well as creating ultra-realistic image re-rendering pipelines for seamless furniture integration in various environments. You will collaborate closely with product and design teams to meet requirements and provide impactful AI-powered solutions. Additionally, you will research and implement cutting-edge generative AI techniques for photorealistic image synthesis, train, fine-tune, and deploy models for high accuracy and performance, and develop scalable APIs and systems to integrate model capabilities into production workflows. To excel in this role, you should have 3-4 years of experience in Generative AI with a focus on diffusion models and demonstrable expertise in furniture or object replacement and re-rendering using generative models. Proficiency in frameworks like PyTorch, expertise in fine-tuning diffusion models, distributed training using CUDA, knowledge of GANs, NeRF, or other generative models, familiarity with 3D rendering pipelines, and proficiency in working with large datasets are essential skills required. Strong analytical and problem-solving skills, excellent communication, and the ability to articulate complex ideas clearly, as well as a proactive and collaborative mindset for teamwork, are valuable soft skills for this role.,

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