Machine Learning Engineer
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About the Role
Key Responsibilities
Design, develop, and operationalize machine learning models to support digital product features and analytics capabilities
Build and maintain end-to-end ML pipelines, including data preparation, model training, validation, and deployment
Develop and expose inference services via APIs for real-time and batch use cases
Implement model monitoring, performance evaluation, and lifecycle management practices
Optimize models and pipelines for scalability, reliability, and efficiency in production environments
Collaborate closely with cross-functional teams to translate business requirements into ML solutions
Maintain clear documentation across model design, processes, and deployment workflow
Required Qualifications
Strong programming skills in Python for model development and data processing
Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn
Experience deploying models into production environments using APIs or containerized services
Familiarity with building data pipelines for feature engineering and model training
Understanding of MLOps practices, including CI/CD, monitoring, and automated workflows
Experience working with cloud platforms and distributed computing tools
Strong analytical and problem-solving skills with attention to detail
Preferred Qualifications
Experience with ML model monitoring tools and model drift detection
Knowledge of data versioning tools (e.g., DVC, MLflow)
Familiarity with microservices and container orchestration (e.g., Docker, Kubernetes)
Exposure to real-world ML deployment challenges and optimizations
About the Company / Team
Singapore
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