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 teams engineering standards.

Bachelors 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

Required Experience:

IC