Machine Learning Engineer

About the Role

We’re looking for a Machine Learning Engineer to develop and optimize advanced AI solutions focused on computer vision, image processing, and video generation. You’ll work with transformers, GANs, and generative AI architectures to build scalable, high-quality video AI solutions at TrueFan AI.

Key Responsibilities

• Design, develop, and optimize machine learning and deep learning models for computer vision and video-based applications.
• Build solutions for image processing, video analysis, facial detection, face tracking, facial landmarks, and related vision tasks.
• Develop and optimize Image-to-Video (I2V) generation models to transform static images into realistic, temporally consistent video sequences. Work on video synthesis, face animation, lip synchronization, and audio-video alignment, where relevant.
• Experience with CNN architectures, conditional generation, and flow-based generative models.
• Develop and optimize image and video processing pipelines for quality, performance, and scalability.
• Work with Transformers, Generative Adversarial Networks (GANs), diffusion models, and other generative architectures for visual content generation and manipulation.
• Optimize model inference, GPU utilization, latency, and computational efficiency for real-time or large-scale video processing.
• Prepare datasets, implement preprocessing and augmentation techniques, and evaluate model performance.
• Integrate trained models into production systems through APIs and scalable inference pipelines.
• Collaborate with AI, backend engineering, and product teams to deliver reliable, production-ready solutions.
• Research emerging computer vision and video AI techniques and translate promising approaches into practical applications.

Requirements & Tech Stack

• Strong programming skills in Python.
• Hands-on experience in Computer Vision, Image Processing, and Video Processing.
• Strong understanding of deep learning concepts, neural networks, and model evaluation.
• Experience with OpenCV and libraries for image/video manipulation and analysis.
• Understanding of image transformations, feature extraction, object detection, segmentation, tracking, and facial analysis.
• Familiarity with video codecs, frame extraction, image sequences, and video processing pipelines.
• Ability to debug, optimize, and deploy ML models in production environments.
• Experience with Transformers, Generative Adversarial Networks (GANs), diffusion models, or vision transformers.
• Familiarity with FFmpeg, GPU acceleration, CUDA, and inference optimization.
• Experience with ONNX, TensorRT, model quantization, or other model-serving optimization techniques.
• Knowledge of Docker, cloud infrastructure, and ML deployment practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, AI/ML, or a related technical field from top tier university or institute.
• Experience with face detection, facial landmarks, face tracking, face swapping, or face reenactment.
• Knowledge of lip-sync generation, talking-head animation, and audio-video synchronization.