
AI Content Generation Specialist
1 day ago
This is a unique opportunity to join our team of experts in developing cutting-edge generative AI models. As a Generative AI Engineer, you will be responsible for designing, training, and deploying advanced machine learning models that generate high-quality, human-like content.
Key Responsibilities:
- Design and develop generative AI models using frameworks such as TensorFlow or PyTorch.
- Collaborate with cross-functional teams to integrate these models into our products, enhancing their capabilities and delivering exceptional value to our clients.
- Conduct research to stay updated on the latest advancements in generative AI and apply best practices to improve model performance.
- Implement and maintain scalable machine learning pipelines for training and deploying models in production environments.
- Evaluate and fine-tune models to ensure they meet performance, accuracy, and efficiency standards.
- Perform data preprocessing, augmentation, and annotation to prepare high-quality datasets for model training.
- Troubleshoot and resolve issues related to model performance, data quality, and integration with other systems.
Qualifications:
- Bachelor's or Master's degree in Computer Science, Machine Learning, Artificial Intelligence, or a related field.
- Proven experience in developing and deploying generative AI models using frameworks such as TensorFlow or PyTorch.
- Strong programming skills in Python and proficiency with machine learning libraries and tools.
- Familiarity with natural language processing (NLP), computer vision, and other relevant AI techniques.
- Experience with cloud platforms such as AWS or Google Cloud for model deployment and management.
- Knowledge of data preprocessing, feature engineering, and model evaluation techniques.
- Excellent problem-solving skills and the ability to work independently and as part of a team.
- Strong communication skills to effectively convey technical concepts to non-technical stakeholders.
Preferred Qualifications:
- Experience with GANs (Generative Adversarial Networks), VAEs (Variational Autoencoders), and other advanced generative models.
- Understanding of ethical considerations and bias mitigation in AI systems.
- Contributions to open-source projects or publications in relevant conferences/journals.
- Experience with MLOps practices and tools for continuous integration and deployment of machine learning models.
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