Job Descriptions:
- Conduct research and evaluation of generative AI algorithms and tools for synthetic data generation
- Stay updated on industry trends and emerging technologies to recommend the best solutions for various data generation needs
- Develop and implement AI models for data generation
- Ensure models are robust, scalable, and meet the specific data requirements of each project
- Design, build, and optimize data generation pipelines to enhance the efficiency and scalability of the synthetic data creation process
- Continuously improve pipeline performance through iterative testing and feedback
- Collaborate with data engineers to ensure the quality and integrity of generated data
- Establish validation processes and mechanisms to maintain high standards of data accuracy
- Conduct performance testing and optimization of generative AI models to achieve high-quality outputs
- Integrate generative AI models and solutions into existing data generation workflows
- Work closely with stakeholders to ensure seamless operation and compatibility within the broader data ecosystem
- Provide technical guidance and support to clients and development teams
- Share best practices, troubleshoot issues, and offer expertise to ensure successful project outcomes
Job Requirements:
- Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or a related field
- Proven experience with generative AI algorithms and synthetic data generation
- Strong programming skills in Python, R, or similar languages commonly used in AI and data science
- Experience in designing and optimizing data pipelines, as well as integrating AI models into existing workflows
- Excellent problem-solving skills with the ability to conduct performance testing and optimization of AI models
- Strong communication and collaboration skills to effectively work with cross-functional teams and clients
- Ability to stay updated with the latest advancements in generative AI and synthetic data generation
