Machine Learning Engineer

6 days 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 high-quality data that drives accurate results.
  • Feature Engineering: Identify and create meaningful features that improve model performance, using your knowledge of data science and machine learning techniques.
  • Model Training & Evaluation: Train machine learning models, tune hyperparameters, and evaluate their performance using appropriate metrics, ensuring that models meet business requirements.
  • 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: Work closely with data scientists, software engineers, and other stakeholders to integrate machine learning models into existing systems, ensuring seamless integration and high-quality results.
  • Research & Innovation: Stay updated with the latest advancements in machine learning, AI, and related fields, and apply new techniques to improve existing models and processes, driving innovation and growth.
  • Performance Monitoring: Monitor the performance of deployed models and update them as needed to ensure they continue to meet business needs, using your expertise in data analysis and machine learning.
  • Documentation: Document models, processes, and results for future reference and to ensure transparency, using clear and concise language that is easily understood by non-technical stakeholders.
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.

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