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Machine Learning Engineer

2 months ago

Singapur, 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 machine learning models that drive business growth and improve customer experiences.

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 data quality and integrity.
  • Feature Engineering: Identify and create meaningful features that improve model performance, driving business insights and decision-making.
  • Model Training & Evaluation: Train machine learning models, tune hyperparameters, and evaluate their performance using appropriate metrics, ensuring model accuracy and reliability.
  • Model Deployment: Deploy machine learning models to production environments, ensuring scalability and reliability, and collaborating with cross-functional teams to integrate models into existing systems.
  • Collaboration & Innovation: Work closely with data scientists, software engineers, and other stakeholders to integrate machine learning models into existing systems, and stay updated with the latest advancements in machine learning, AI, and related fields, applying new techniques to improve existing models and processes.
  • Performance Monitoring: Monitor the performance of deployed models and update them as needed to ensure they continue to meet business needs, and document models, processes, and results for future reference and to ensure transparency.
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.
    • Hands-on experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.
    • Proficiency in programming languages such as Python, R, or Java.
    • Experience with data preprocessing, feature engineering, and model evaluation.
  • Skills:
    • Strong understanding of machine learning algorithms and techniques (e.g., regression, classification, clustering, deep learning).
    • Requires strong programming skills and expertise in data science.
    • Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau.
    • Familiarity with cloud platforms such as AWS, Azure, or GCP.
    • Knowledge of version control systems such as Git.
    • Excellent problem-solving skills and the ability to work independently and in a team.
    • Strong communication skills to explain complex concepts to non-technical stakeholders.
Preferred Qualifications:
  • Experience with big data technologies such as Hadoop, Spark, or Kafka.
  • Knowledge of natural language processing (NLP) or computer vision.
  • Experience with containerization and orchestration tools like Docker and Kubernetes.
  • Familiarity with MLOps practices and tools.