Machine Learning Engineer
Current• Building MLOps in Technology Financial Company• Building and maintaining MLOps infrastructure (Kubernetes cluster for serving API, training pipeline, and development) and platform (Airflow, Database, and repo management)• Responsible for developing and maintaining the product APIs such as Voucher and Product Recommendations, Fraud Detection and Scam Scoring, Credit Score, Face Comparison, etc. The scope of maintaining such as: - Designing the API system to meet the requirements of stakeholders. - Develop and maintain a fast and robust API for current and upcoming projects. - Testing the API case and performance for achieving the desired output and performance. - Build CI/CD for easy integration and deployment. - Managing the cluster infrastructure. - Create a monitoring dashboard. - Create alerting that integrates with the group channel. - Make sure the APIs are scalable and have 100% uptime.• Maintaining our scheduled Machine Learning training and prediction pipeline products (Recommendation, Fraud Detection, Scam Score, Intent Classification, etc) with/without distributed computing (Python Package/Pyspark) using Airflow and/or GitLab CI/CD.• Pair and collaborate with the Product and Project Management, Data Scientist, Data Engineer, Data Quality/Governance, Data Analyst, Site Reliability Engineer, Back End, and IT Security team to maintain and develop all the Machine Learning Engineer products.• Write technical documentation and report it to the team leader, and the VP of Data.