- Conduct in-depth research and experimentation with state-of-the-art GenAI models for both open source and closed source, exploring various architectures, loss functions, regularization techniques, and training strategies.
- Design and implement custom GenAI models tailored to specific domains and tasks, considering factors such as data type, structure, and desired output characteristics including accuracy and business benefits.
- Optimize and fine-tune GenAI models to achieve high-quality, diverse, and visually appealing output.
- Experiment with techniques like progressive growing, self-attention mechanisms, or unsupervised learning to improve model performance.
- Investigate and implement techniques for controlling the output of generative models, such as vectorized embeddings, conditional generation, style transfer, or interactive editing of generated samples.
- Regularly analyze, evaluate, and retrain the GenAI models using quantitative metrics and qualitative assessments.
- Continuously iterate on model architectures and training methodologies to enhance their robustness, generalization, and ability to capture intricate patterns and details from the input data.
- Salary Offer 0 ~ $3000
- Experience Level Junior
- Total Years Experience 0-5
- Dropdown field Option 1