FUNCTIONAL COMPETENCIES
AI Model Development
- Design, build, and deploy AI/ML models (Machine Learning, Deep Learning) for business applications.
- Research and experiment with state-of-the-art algorithms to solve complex business problems.
- Customize and fine-tune models for specific use cases.
Data Engineering
- Collect, process, clean, and standardize data from various sources (structured, unstructured, streaming).
- Develop and maintain data pipelines for AI projects.
- Work with big data tools and platforms (e.g., Spark, Hadoop, cloud data services).
Model Evaluation & Optimization
- Evaluate model performance using appropriate metrics and validation techniques.
- Optimize algorithms for accuracy, speed, and scalability.
- Conduct A/B testing and model comparisons to select the best solution.
AI Solution Deployment
- Deploy AI solutions in production environments (on-premises or cloud).
- Build and maintain APIs for model integration.
- Monitor deployed models and ensure reliability, scalability, and security.
Collaboration with Cross-functional Teams
- Collaborate with cross-functional teams (Business, IT, Data Analytics, Operations, etc.) to identify needs and define project requirements.
- Communicate technical concepts and results to non-technical stakeholders.
- Provide technical guidance and support to team members.Collaborate with Finance, Sales, Marketing, SCM, Purchasing, Operations, Technical, Internal Control, IT and other teams to ensure data-driven decision-making.
Documentation & Reporting
- Document development processes, experiment results, and AI solutions.
- Prepare regular reports on project outcomes, model performance, and business impact.
- Maintain clear and comprehensive technical documentation for future reference.
Research & Innovation
- Stay updated with the latest advancements in AI, ML, and data science.
- Propose and implement innovative solutions to improve business processes.
- Participate in knowledge sharing and training sessions within the organization.
Ethical AI & Compliance
- Ensure AI solutions comply with relevant data privacy, security, and ethical standards.
- Assess and mitigate risks related to bias, fairness, and transparency in AI models.
Continuous Improvement
- Continuously monitor and improve existing AI systems.
- Gather feedback from users and stakeholders to enhance solution effectiveness.
- Identify opportunities for automation and process optimization using AI.
SPECIAL REQUIREMENTS
- Education: Bachelor's degree in Computer Science, Data Science, Applied Mathematics, or related fields. Solid foundation in AI, Machine Learning, Deep Learning is preferred.
- Experience: At least 1 year of experience in developing real-world AI/ML projects. Proficient in Python (TensorFlow, PyTorch, Scikit-learn), SQL, and big data tools.
- Communication & Presentation skills: Excellent communication skills to present technical results to non-technical stakeholders.
- Programming Skills: Strong skills in Python, R, or other AI programming languages. Experience building APIs and deploying models on cloud platforms (Azure, AWS, GCP).
- Other Accountability: Strong problem-solving mindset, proactive in learning new technologies and keeping up with AI trends.
- Language skills: Good English skills (reading technical documents, communicating with international teams).
