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Senior Machine Learning Engineer @ Hogwarts E-learning

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 Senior Machine Learning Engineer

Job Description

Location: Gurugram (Work From Office)
Job Type: Full-Time


Job Description:

As a Senior Machine Learning Engineer, you will be responsible for designing, developing, and deploying cutting-edge models for end-to-end content generation, including AI-driven image/video generation, lipsyncing, and multimodal AI systems. You will work on the latest advancements in deep generative modeling to create highly realistic and controllable AI-generated media.

Responsibilities:

  • Research & Develop: Design and implement state-of-the-art generative models, including Diffusion Models, 3D VAEs and GANs for AI-powered media synthesis.
  • End-to-End Content Generation: Build and optimize AI pipelines for high-fidelity image/video generation and lipsyncing using diffusion and autoencoder models.
  • Speech & Video Synchronization: Develop advanced lipsyncing and multimodal generation models that integrate speech, video, and facial animation for hyper-realistic AI-driven content.
  • Real-Time AI Systems: Implement and optimize models for real-time content generation and interactive AI applications using efficient model architectures and acceleration techniques.
  • Scaling & Production Deployment: Work closely with software engineers to deploy models efficiently on cloud-based architectures (AWS, GCP, or Azure).
  • Collaboration & Research: Stay ahead of the latest trends in deep generative models, diffusion models, and transformer-based vision systems to enhance AI-generated content quality.
  • Experimentation & Validation: Design and conduct experiments to evaluate model performance, improve fidelity, realism, and computational efficiency, and refine model architectures.
  • Code Quality & Best Practices: Participate in code reviews, improve model efficiency, and document research findings to enhance team knowledge-sharing and product development.

Qualifications:

  • Bachelor's or Masters degree in Computer Science, Machine Learning, or a related field.
  • 3+ years of experience working with deep generative models, including Diffusion Models, 3D VAEs, GANs and autoregressive models.
  • Strong proficiency in Python and deep learning frameworks such as PyTorch.
  • Expertise in multi-modal AI, text-to-image, and image-to-video generation, audio to lipsync
  • Strong understanding of machine learning principles and statistical methods.
  • Good to have experience in real-time inference optimization, cloud deployment, and distributed training.
  • Strong problem-solving abilities and a research-oriented mindset to stay updated with the latest AI advancements.
  • Familiarity with generative adversarial techniques, reinforcement learning for generative models, and large-scale AI model training.

Preferred Qualifications:

  • Experience with transformers and vision-language models (e.g., CLIP, BLIP, GPT-4V).
  • Background in text-to-video generation, lipsync generation and real-time synthetic media applications.
  • Experience in cloud-based AI pipelines (AWS, Google Cloud, or Azure) and model compression techniques (quantization, pruning, distillation).
  • Contributions to open-source projects or published research in AI-generated content, speech synthesis, or video synthesis.

Job Classification

Industry: Film / Music / Entertainment
Functional Area / Department: Media Production & Entertainment
Role Category: Media Production & Entertainment - Other
Role: Media Production & Entertainment - Other
Employement Type: Full time

Contact Details:

Company: Hogwarts E-learning
Location(s): Noida, Gurugram

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Keyskills:   Speech Recognition Gan Variational Autoencoders Image Processing Computer Vision Stable Diffusion Deep Learning

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Hogwarts E-learning

About Us: TrueFan is at the forefront of AI-driven content generation, leveraging cutting-edge generative models to build next-generation products. Our mission is to redefine content generation space through advanced AI technologies, including deep generative models, text-to-video and image-to-vide...