- Problem Identification and Solution Design:
- Collaborate with stakeholders to identify business problems and opportunities where AI and machine learning techniques can be applied effectively.
- Design AI solutions and algorithms to address specific use cases, optimize processes, and achieve business objectives.
- Data Collection and Preparation:
- Collect, clean, preprocess, and analyze data from various sources to create high-quality datasets for AI model training and evaluation.
- Implement data transformation and feature engineering techniques to extract relevant insights and patterns from raw data.
- Model Development and Training:
- Develop, implement, and train machine learning and deep learning models using frameworks such as TensorFlow, PyTorch, scikit-learn, or similar.
- Fine-tune model parameters, optimize hyperparameters, and evaluate model performance using appropriate metrics and validation techniques.
- Model Deployment and Integration:
- Deploy trained AI models into production environments, ensuring scalability, reliability, and efficiency.
- Integrate AI solutions with existing systems, applications, and workflows to enable seamless data exchange and interaction.
- Monitoring and Maintenance:
- Monitor the performance and accuracy of deployed AI models, and implement measures to address drift, degradation, or bias over time.
- Provide ongoing maintenance and support for AI solutions, including troubleshooting issues and implementing updates or enhancements.
- Ethical and Responsible AI:
- Ensure that AI solutions adhere to ethical and regulatory guidelines, and mitigate risks related to bias, fairness, transparency, and privacy.
- Implement mechanisms for model explainability and accountability to enhance trust and reliability in AI-driven decision-making.
- Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, Statistics, or a related field. A Ph.D. in a relevant discipline may be required for advanced research roles.
- Proficiency in programming languages such as Python, R, Java, or Scala.
- Strong understanding of machine learning, deep learning, and statistical modeling techniques.
- Experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, scikit-learn, or Keras.
- Knowledge of data processing and analysis tools such as pandas, NumPy, and SQL.
- Experience in Tableau.
- Strong analytical and problem-solving skills to understand complex data problems and design effective AI solutions.
- Ability to interpret data, identify patterns, and derive actionable insights to inform decision-making.
- Excellent communication and interpersonal skills to collaborate effectively with cross-functional teams, stakeholders, and clients.
- Ability to translate business requirements into technical specifications and vice versa, and communicate technical concepts to non-technical audiences.
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Paglalarawan
PLS REVIEW THE JOB DETAILS AND WORKING CONDITIONS BEFORE SENDING APPLICATIONWork Set-up: Full On-site
Work Schedule: Mon- Friday (With duty on Weekday Holidays)
Work Time: 10:00 AM - 7:00 PM (Fixed)
Overtime Eligibility: No
Salary Range Offer: 60, ,000 php per month (Final offer will vary but will not go lower or higher than this range)
KEY RESPONSILIBILITIES
Educational Background:Â
Technical Skills
Analytical and Problem-Solving Skills: