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Machine Learning Engineer

2 months ago

Singapore RiceBowl Full time
Job Summary:

RiceBowl is seeking a highly skilled Machine Learning Engineer to join our team. As a key member of our data science team, you will be responsible for designing, developing, and deploying scalable machine learning solutions that drive business growth.

Key Responsibilities:
  • Model Development: Design and develop machine learning models and algorithms to solve complex business problems, leveraging your expertise in statistical analysis and software engineering.
  • Data Preprocessing: Clean, preprocess, and analyze large datasets to be used for training models, ensuring high-quality data that drives accurate results.
  • Feature Engineering: Identify and create meaningful features that improve model performance, driving business value through data-driven insights.
  • Model Training & Evaluation: Train machine learning models, tune hyperparameters, and evaluate their performance using appropriate metrics, ensuring models meet business needs.
  • Model Deployment: Deploy machine learning models to production environments, ensuring scalability and reliability, and monitoring performance to drive continuous improvement.
  • Collaboration: Work closely with data scientists, software engineers, and other stakeholders to integrate machine learning models into existing systems, driving business outcomes through collaboration.
  • Research & Innovation: Stay updated with the latest advancements in machine learning, AI, and related fields, applying new techniques to improve existing models and processes, and driving innovation through data-driven insights.
  • Performance Monitoring: Monitor the performance of deployed models and update them as needed to ensure they continue to meet business needs, driving continuous improvement through data-driven decision making.
  • Documentation: Document models, processes, and results for future reference and to ensure transparency, driving business value through data-driven insights.
Qualifications:
  • Education: Bachelor's or Master's degree in Computer Science, Data Science, Mathematics, Statistics, or a related field.
  • Experience: 2+ years of experience in machine learning, data science, or related roles, with hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Skills: Strong understanding of machine learning algorithms and techniques, proficiency in programming languages such as Python, R, or Java, and experience with data preprocessing, feature engineering, and model evaluation.
  • Preferred Qualifications: Experience with big data technologies such as Hadoop, Spark, or Kafka, knowledge of natural language processing (NLP) or computer vision, and experience with containerization and orchestration tools like Docker and Kubernetes.