Advanced AI Face Swap Application
Budget: $1,500 – $3,000 USD
https://drive.google.com/drive/u/1/?pli=1
Please download the files from this Drive link to verify whether or not you are able to complete the task.
Since the driver login credentials are private, simply running the .bat file included in the attachment will automatically log you in. Please place a proposal *only* if you have read the job description in its entirety. You must include the word "Checking" at the very beginning of your bid.
Project Overview
We are seeking an experienced AI/ML Engineer to develop a high-quality Face Swap application using state-of-the-art deep learning techniques. The goal is to create a robust, scalable, and realistic face-swapping solution capable of processing images and videos with high accuracy while preserving natural facial expressions, lighting, skin tones, and identity consistency.
Responsibilities
Design and develop AI-powered face-swapping algorithms.
Implement and fine-tune deep learning models for face detection, face alignment, face segmentation, and face replacement.
Optimize image and video processing pipelines for high-quality output.
Ensure realistic blending of facial features, expressions, and lighting conditions.
Improve model performance, inference speed, and scalability.
Integrate the solution into a web application, desktop application, or API service.
Conduct testing and quality assurance to ensure production-ready performance.
Required Skills
Strong experience with Python and machine learning frameworks such as PyTorch or TensorFlow.
Experience with computer vision libraries including OpenCV, MediaPipe, Dlib, or similar.
Knowledge of GANs, diffusion models, face recognition, facial landmark detection, and image synthesis.
Experience with face-swapping technologies such as InsightFace, SimSwap, FaceFusion, Roop, DeepFaceLab, or custom implementations.
Understanding of GPU acceleration, CUDA, and model optimization techniques.
Experience building REST APIs and deploying AI models to cloud environments.
Familiarity with Docker, Linux, and MLOps practices.
Preferred Qualifications
Experience with real-time video face swapping.
Experience deploying AI applications on AWS, Azure, or GCP.
Knowledge of video processing frameworks such as FFmpeg.
Experience optimizing models for mobile or edge devices.
Deliverables
Complete source code with documentation.
Trained and optimized face swap models.
Image face-swapping functionality.
Video face-swapping functionality.
API or application interface for end users.
Deployment guide and technical documentation.
Testing report and performance benchmarks.
Project Goals
High-quality, realistic face swaps.
Fast processing speed.
Support for multiple image and video formats.
Scalable architecture for future enhancements.
Production-ready solution suitable for commercial use.
When Applying
Please include:
Relevant AI/Computer Vision projects.
Examples of face swap or image generation work.
Technology stack you plan to use.
Estimated timeline and budget.
Experience with large-scale AI deployments.
Please download the files from this Drive link to verify whether or not you are able to complete the task.
Since the driver login credentials are private, simply running the .bat file included in the attachment will automatically log you in. Please place a proposal *only* if you have read the job description in its entirety. You must include the word "Checking" at the very beginning of your bid.
Project Overview
We are seeking an experienced AI/ML Engineer to develop a high-quality Face Swap application using state-of-the-art deep learning techniques. The goal is to create a robust, scalable, and realistic face-swapping solution capable of processing images and videos with high accuracy while preserving natural facial expressions, lighting, skin tones, and identity consistency.
Responsibilities
Design and develop AI-powered face-swapping algorithms.
Implement and fine-tune deep learning models for face detection, face alignment, face segmentation, and face replacement.
Optimize image and video processing pipelines for high-quality output.
Ensure realistic blending of facial features, expressions, and lighting conditions.
Improve model performance, inference speed, and scalability.
Integrate the solution into a web application, desktop application, or API service.
Conduct testing and quality assurance to ensure production-ready performance.
Required Skills
Strong experience with Python and machine learning frameworks such as PyTorch or TensorFlow.
Experience with computer vision libraries including OpenCV, MediaPipe, Dlib, or similar.
Knowledge of GANs, diffusion models, face recognition, facial landmark detection, and image synthesis.
Experience with face-swapping technologies such as InsightFace, SimSwap, FaceFusion, Roop, DeepFaceLab, or custom implementations.
Understanding of GPU acceleration, CUDA, and model optimization techniques.
Experience building REST APIs and deploying AI models to cloud environments.
Familiarity with Docker, Linux, and MLOps practices.
Preferred Qualifications
Experience with real-time video face swapping.
Experience deploying AI applications on AWS, Azure, or GCP.
Knowledge of video processing frameworks such as FFmpeg.
Experience optimizing models for mobile or edge devices.
Deliverables
Complete source code with documentation.
Trained and optimized face swap models.
Image face-swapping functionality.
Video face-swapping functionality.
API or application interface for end users.
Deployment guide and technical documentation.
Testing report and performance benchmarks.
Project Goals
High-quality, realistic face swaps.
Fast processing speed.
Support for multiple image and video formats.
Scalable architecture for future enhancements.
Production-ready solution suitable for commercial use.
When Applying
Please include:
Relevant AI/Computer Vision projects.
Examples of face swap or image generation work.
Technology stack you plan to use.
Estimated timeline and budget.
Experience with large-scale AI deployments.
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