Key Responsibilities:

1. Generative AI and ML Development

• Design, develop, and implement GenAI models and applications
• Optimize existing GenAI systems for improved performance and efficiency
• Stay current with the latest advancements in GenAI technologies
• Create and manage the AI/ML development process and infrastructure
   

2. Collaboration and Communication

• Work closely with data scientists, programmers, and other stakeholders
• Communicate the utility of AI models to diverse audiences, including product managers and executives
• Translate complex technical concepts into accessible language for non-technical team members
   

3. Data Analysis and Infrastructure

• Conduct statistical analysis and interpret findings to drive decision-making
• Create and manage data transformation infrastructure
• Automate critical tasks and procedures for the data science team
   

4. Model Deployment and Integration

• Expose machine learning and GenAI models via APIs for integration with other applications
• Develop and maintain API documentation for seamless integration
• Collaborate on system integration projects to ensure smooth implementation of AI solution

5. Innovation and Research

• Explore new GenAI techniques and methodologies to enhance product capabilities
• Contribute to the company's AI strategy and roadmap
   

6. Evaluation 

• Develop and implement testing protocols for GenAI models
• Ensure the reliability, scalability, and performance of AI systems
• Conduct regular audits of AI models to maintain accuracy and ethical standards
   

Requirement:

• Master's or Bachelor's degree in Computer Science, Computer Engineering, Artificial Intelligence, or a closely related field
• 6-8 years of relevant work experience in software development, with a focus on AI  and frontend technologies
• Minimum of 4+ years' experience in a similar role involving AI development and  implementation
• Strong background in AI, particularly in Generative AI technologies
• Experience with natural language processing (NLP) and computer vision
• Knowledge of ethical AI practices and data privacy regulations
• Solid knowledge of data warehousing, database systems, and cloud platforms (e.g., AWS, Azure, or GCP)
• Experience with data mining techniques and methodologies
• Excellent organizational and analytical abilities
• Outstanding problem-solving skills, with the ability to tackle complex technical challenges
• Strong statistical analysis skills and the ability to interpret findings effectively