Machine Learning Engineer

●Collaborate with Machine Learning Engineers, Backend Engineers, Data Scientists, and Product Managers to develop AI-powered features and services. ● Build, deploy, and maintain production-ready machine learning models that improve allocation, ETA prediction, demand forecasting, and marketplace optimization. ● Develop scalable data processing, feature engineering, and model training pipelines for large-scale datasets. ● Integrate machine learning models into backend services and ensure reliable, low-latency inference in production ● Monitor model performance, identify model drift, and continuously improve model accuracy and operational reliability. ● Contribute to MLOps practices including model versioning, automated deployment, monitoring, and experimentation. ● Write clean, maintainable, and well-tested code while following software engineering best practices. ● Participate in technical discussions, code reviews, and knowledge sharing to continuously improve the team's engineering standards. ● Bachelor's degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field. ● At least 3 years of professional experience building and deploying machine learning applications in production. ● Strong proficiency in Python and experience with machine learning frameworks such as PyTorch, TensorFlow, or Scikit-learn. ● Experience with SQL and data processing frameworks for working with large datasets. ● Familiarity with model deployment, REST APIs, Docker, Kubernetes, and cloud-based infrastructure. ● Understanding of MLOps concepts including model lifecycle management, monitoring, CI/CD, and experimentation. ● Solid software engineering fundamentals including version control, testing, debugging, and system design. ● Strong analytical, problem-solving, and communication skills with the ability to work effectively in cross-functional teams. Why join Angkas? Freedom of work Work-life balance Free meals and use of gym Opportunities for promotion Competitive salary Pay raise Start-up environment Multi-cultural and Agile work environment Diversified use of technology