Job Title: AI/ML Engineer
Job Summary:
We are looking for an experienced AI/ML Engineer to design, develop, and deploy machine
learning models and systems specifically tailored for generating realistic mannequin-style apparel
images. This role will involve working with state-of-the-art generative models (e.g., GANs,
diffusion models) and image processing techniques to create a scalable and efficient system that can
transform diverse apparel inputs into consistent, high-quality, and visually appealing mannequin
presentations.
Responsibilities:
- Conduct research into cutting-edge AI/ML techniques for image generation, particularly
focusing on generative adversarial networks (GANs), diffusion models, and other relevant
architectures for realistic apparel synthesis.
- Design, implement, train, and optimize deep learning models for generating apparel images on
virtual or AI-generated mannequins.
- Work with large datasets of apparel images and mannequin data, including data cleaning,
augmentation, and preparation for model training.
- Contribute to the design and development of scalable and robust AI systems and infrastructure
for image generation, including API integration and deployment.
- Establish and implement metrics for evaluating the quality, realism, and consistency of
generated images, and iterate on models based on performance.
- Work closely with cross-functional teams, including product managers, designers, and other
engineers, to understand requirements and deliver impactful solutions.
- Optimize models for efficiency, speed, and resource utilization for real-time or near real-time
generation.
Required Skills and Qualifications:
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning,
Electrical Engineering, or a related quantitative field.
4+ years of professional experience in AI/ML engineering, with a strong focus on deep learning
and computer vision.
Proven experience with generative models (e.g., GANs, VAEs, Diffusion Models) for image
synthesis and manipulation.
Proficiency in deep learning frameworks such as TensorFlow, PyTorch, or JAX.
Strong programming skills in Python.
Experience with image processing libraries (e.g., OpenCV, Pillow).
Solid understanding of machine learning principles, algorithms, and data structures.
Experience with cloud platforms (AWS, GCP, Azure) for ML model training and deployment.
Excellent problem-solving skills and the ability to work independently as well as in a team
environment.
Strong communication and presentation skills.
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