Job summary

Job Responsibilities:

• Design, develop, and implement generative AI models, such as GANs, VAEs, Diffusion Models, and Transformers, for various applications including but not limited to text, image, and audio generation.
• Collaborate with cross-functional teams, including data scientists, machine learning engineers, and software developers, to build end-to-end AI solutions.
• Conduct research and stay up-to-date with the latest advancements in the field of generative AI and machine learning.
• Fine-tune pre-trained models and develop custom architectures to improve performance and scalability.
• Analyze and process large datasets to train models and ensure data quality and consistency.
• Deploy and optimize AI models in production environments, ensuring reliability, efficiency, and scalability.
• Troubleshoot, debug, and enhance models and algorithms based on user feedback and real-world performance.
• Document the development process, models, and algorithms, ensuring code and models are well-documented for future reference.

Qualifications:

• Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Ph.D. is a plus.
• 5+ years of experience in developing and deploying machine learning and deep learning models, with at least 2 years focused on generative AI.
• Strong programming skills in Python and familiarity with deep learning frameworks such as TensorFlow, PyTorch, and JAX.
• Experience with transformer models (e.g., GPT, BERT, T5) and generative models (e.g., GANs, VAEs, Diffusion Models).
• Solid understanding of neural networks, machine learning algorithms, and statistical analysis.
• Experience with cloud platforms like AWS, Azure, or Google Cloud, including model deployment and scaling.
• Familiarity with data processing tools and libraries (e.g., Pandas, NumPy, OpenCV, Hugging Face).
• Strong problem-solving skills and ability to work independently as well as in a collaborative team environment.
• Excellent communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.

Preferred Skills:

• Experience in natural language processing (NLP) or computer vision (CV).
• Familiarity with reinforcement learning or other advanced machine learning techniques.
• Experience with MLOps tools and practices for managing the lifecycle of AI models.
• Knowledge of software development best practices, including version control (Git), continuous integration/continuous deployment (CI/CD), and containerization (Docker, Kubernetes).

Why Join Us?

• Work on exciting projects that leverage the latest in AI technology.
• Be part of a dynamic, innovative, and diverse team.
• Opportunities for continuous learning and professional development.
• Competitive salary, benefits, and flexible working arrangements.