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
