Develop and optimize generative AI and machine learning models, infrastructure, APIs, and integrations. Perform statistical analysis, data transformation, automation, model testing, audits, and evaluation for reliability, scalability, accuracy, and ethical compliance. Collaborate with technical and business stakeholders, communicate AI concepts clearly, research emerging techniques, and contribute to AI strategy and product capabilities.
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
Income Insurance Singapore, Singapore, SGP Office
75 Bras Basah Road, Singapore, Singapore, Singapore, 189557
Income Insurance Singapore Office
Singapore
Income Insurance Singapore, Singapore, SGP Office
1 Paya Lebar Link, #07-01 PLQ 1 Paya Lebar Quarter, Singapore, Singapore, Singapore, 408533
Income Insurance Singapore, Singapore, SGP Office
2 Tampines Central 6, #01-01 NTUC Income Tampines Point, Singapore, Singapore, Singapore, 529483
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What you need to know about the Singapore Tech Scene
The digital revolution has driven a constant demand for tech professionals across industries like software development, data analytics and cybersecurity. In Singapore, one of the largest cities in Southeast Asia, the demand for tech talent is so high that the government continues to invest millions into programs designed to develop a talent pipeline directly from universities while also scaling efforts in pre-employment training and mid-career upskilling to expand and elevate its workforce.
