Data AI Engineer

Job Title: Data AI Engineer (Middle Level: 3–5 Years of Experience)Location: Jakarta - Full WFODepartment: Data & TechnologyEmployment Type: Contract (6 months, extendable) - Immediate HiringAbout the RoleWe are seeking a skilled Data AI Engineer to strengthen our data-driven decision-making, model development, and AI implementation initiatives across business units. This role will focus on developing, training, and deploying production-grade machine learning models that support the company’s digital transformation roadmap, including AI automation, recommendation systems, and predictive analytics.ResponsibilitiesCollect, clean, and preprocess large structured and unstructured datasets.Develop, validate, and deploy machine learning and AI models for prediction, classification, clustering, and recommendation purposes.Collaborate with engineering and business teams to translate requirements into data-driven insights and AI solutions.Monitor, optimize, and maintain deployed models to ensure performance and reliability.Build and manage data pipelines and feature stores for production models.Conduct exploratory data analysis (EDA) to identify patterns, trends, and opportunities.Document methodologies and present analytical findings to non-technical stakeholders.Support the development of the company’s AI strategy and contribute to innovation initiatives.Minimum RequirementsBachelor’s Degree (S1) in Information Technology, Computer Science, or a related field (mandatory).Minimum 3 years of experience as a Data Scientist or Machine Learning Engineer.Excellent command of Python, SQL, and key data libraries (Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch).Strong understanding of machine learning algorithms, model evaluation, and feature engineering.Experience with data visualization tools such as Power BI, Tableau, Plotly, or Matplotlib/Seaborn.Working knowledge of cloud-based AI platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).Familiarity with ETL processes, data pipelines, and MLOps concepts (Docker, Airflow, MLflow, CI/CD for ML).Knowledge of big data frameworks (Spark, Databricks, etc.) is a plus.Solid understanding of data governance, security, and privacy compliance.Training or certification in Machine Learning, Deep Learning, or Data Engineering preferred.Proficiency in both Indonesian and English (spoken and written).