Data Science Engineer

2 weeks ago


Singapore AIKIT PTE. LTD. Full time
About This Role
We are seeking a highly skilled AI/ML Engineer to join our team and contribute to the design, development, and deployment of AI/ML models for various applications. As an AI/ML Engineer, you will be responsible for collaborating with cross-functional teams to integrate AI solutions into products and services. You will also conduct research and stay current with AI trends, tools, and techniques to ensure our solutions remain at the forefront of innovation. The ideal candidate will have a Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field and strong programming skills in Python (and optionally R, Java, or C++). Hands-on experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, etc. is also required. Additionally, experience with cloud services such as AWS, Azure, or GCP and familiarity with data engineering tools and pipelines (e.g., Spark, Airflow, Kafka) is desirable. A solid understanding of mathematics and statistics, especially linear algebra, calculus, probability, and optimization, is necessary for success in this role.

Responsibilities
  • Collaborate with cross-functional teams to integrate AI solutions into products and services.
  • Conduct research and stay current with AI trends, tools, and techniques.
  • Develop and deploy AI/ML models for various applications.
  • Optimize model performance by tuning hyperparameters and evaluating results.
  • Implement models in production environments using cloud platforms and scalable architectures.
  • Document processes, models, and experiments in a clear and organized manner.

Requirements
  • Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
  • Strong programming skills in Python (and optionally R, Java, or C++).
  • Hands-on experience with ML frameworks like TensorFlow, PyTorch, Scikit-learn, etc.
  • Experience with cloud services such as AWS, Azure, or GCP.
  • Familiarity with data engineering tools and pipelines (e.g., Spark, Airflow, Kafka).
  • Solid understanding of mathematics and statistics, especially linear algebra, calculus, probability, and optimization.


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