Generative AI Architect

Responsibilities:

1. Develop and implement generative models using large language models to generate high-quality and coherent text, images, or other forms of data.
2. Research, design, and experiment with novel generative AI techniques to improve model performance and output quality.
3. Collaborate with cross-functional teams, including data scientists, machine learning engineers, and software developers, to integrate generative models into various applications and platforms.
4. Train and fine-tune large language models for specific tasks or domains by leveraging transfer learning and domain adaptation techniques.
5. Optimize and scale generative models to handle large datasets and real-time inference requirements.
6. Conduct thorough testing and evaluation of generative models to measure performance, identify limitations, and propose enhancements.
7. Stay up-to-date with the latest advancements in generative AI, deep learning, and large language models, and contribute to knowledge sharing within the team.
8. Document research findings, methodologies, and implementation details for future reference and knowledge transfer.
9. Assist in mentoring and guiding junior team members in the field of generative AI and large language models.

Requirements:

1. Bachelor's degree in Computer Science. A master's or Ph.D. degree is preferred.

2. Strong proficiency in Python programming and experience with deep learning frameworks such as TensorFlow or PyTorch.

3. Solid understanding of generative models, including Variational Autoencoders (VAEs), Generative Adversarial Networks (GANs), and autoregressive models.

4. Experience working with large language models such as GPT-3, GPT-4, or similar models.

5. Proven track record of developing and implementing generative AI models for text, image, or other data types.

6. Familiarity with transfer learning and pre-training techniques for large language models.

7. Strong problem-solving and analytical skills, with the ability to experiment, iterate, and optimize generative models.

8. Excellent communication skills, with the ability to collaborate effectively with cross-functional teams and present complex concepts in a clear and concise manner.

9. Strong publication record or contributions to the generative AI research community is a plus.