• Skilled in programming/scripting using Python programming language
• Skilled in data exploration, analysis, and visualization using Python libraries such as Pandas, NumPy, Matplotlib, Seaborn, Scikit-learn, and other related software libraries
• Should possess outstanding programming skills in text mining, web scraping, data wrangling, and statistical analysis
• Should be familiar with statistical language models (n-grams) and neural network-based language models (LSTM and Transformers)
• Skilled in data cleaning and data preparation methods
• Knowledgeable in different machine learning techniques (classification, clustering, regression, neural networks, etc.), their advantages and disadvantages, and their implementation in Python libraries such as Scikit-learn, Tensorflow, and Keras
• Knowledgeable in deep learning techniques and algorithms for computer vision problems. Experience in applications of deep learning to geospatial and remotely sensed data is a big plus.
• ​Must have technical leadership experience
• Has good communication skills
• Must be able to work well with a team, adaptable to circumstances, fast learner, and self-motivated
• Can work with minimal supervision
• Must be willing to work in Quezon City

Under general supervision and direction, HE/SHE shall perform the following:

• Design neural network architectures and programs and train deep learning algorithms
• Develop Neural Machine Translation models from large corpora
• Report to the technical leads of the project
• Communicate with the stakeholders about the data engineering required for the training of the AI models
• Coordinate with the data engineering team for efficient data processing and AI model development
• Coordinate with the software engineering team for model deployment, model performance monitoring, and visualization
• Collaborate with program team members to identify gaps and structure problems as well as to propose solutions and strategies to business challenges.
• Coordinate with the System Engineering Team for the implementation of the defined machine learning operations system
• Identify, implement, and evaluate existing processes and software frameworks monitoring and analyzing model performance through time
• Conduct informative talks regarding the developed and established processes and software tools for machine learning model development and model performance monitoring
• Write technical documentation about scientific findings during the course of the project implementation
• Report to work on time.