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