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3.0 - 7.0 years
0 Lacs
haryana
On-site
As a Senior Machine Learning Engineer at TrueFan in Gurugram, you will play a crucial role in designing, developing, and deploying cutting-edge models for end-to-end content generation using AI-driven technologies. Your responsibilities will include working on advanced generative models such as Diffusion Models, 3D VAEs, and GANs to create highly realistic AI-generated media. You will collaborate with software engineers to deploy models efficiently on cloud-based architectures and stay updated with the latest trends in deep generative models and transformer-based vision systems to enhance content quality. Your main responsibilities will revolve around designing and implementing state-of-the-art generative models, building AI pipelines for image/video generation and lipsyncing, developing lipsyncing and multimodal generation models for hyper-realistic content, implementing real-time content generation systems, and conducting experiments to evaluate and improve model performance. Additionally, you will participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development. To be successful in this role, you should have a Bachelor's or Master's degree in Computer Science, Machine Learning, or a related field, along with at least 3 years of experience working with deep generative models like Diffusion Models, 3D VAEs, GANs, and autoregressive models. Proficiency in Python and deep learning frameworks such as PyTorch is essential. Strong problem-solving abilities, a research-oriented mindset, and familiarity with generative adversarial techniques, reinforcement learning, and large-scale AI model training are also required. Preferred qualifications include experience with transformers and vision-language models, a background in text-to-video and lipsync generation, familiarity with cloud-based AI pipelines, and contributions to open-source projects or published research in AI-generated content.,
Posted 2 weeks ago
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