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