Develop and implement generative models: The engineer would be responsible for designing and
building generative models that can create realistic and high-quality content, such as text, images,
and audio.
Train and fine-tune models: The engineer would be responsible for training and fine-tuning the
generative models using large datasets to improve their performance and accuracy.
Collaborate with data scientists and researchers: The engineer would collaborate with data
scientists and researchers to understand the requirements and objectives of the project and develop
generative models accordingly.
Deploy models in production: The engineer would be responsible for deploying the generative models
in a production environment and ensuring that they function effectively and efficiently.
Monitor and maintain models: The engineer would monitor and maintain the generative models to
ensure
that they are operating as intended and make necessary changes to improve their performance.
Stay up-to-date with industry developments: The engineer would stay up-to-date with the latest
advancements in the field of generative AI and incorporate them into their work.
Requirements:
A degree in computer science or a related field.
Extensive experience in developing and implementing generative models.
Strong programming skills, particularly in Python and deep learning frameworks such as TensorFlow
and PyTorch.
Excellent analytical and problem-solving skills.
Good communication and collaboration skills.
Familiarity with natural language processing (NLP) and computer vision (CV) technologies.
Experience working with large datasets and cloud computing platforms such as AWS or Google Cloud.
