AI Engineer: ML/NLP for Real-World Impact

Seatrium Digital Pte. Ltd.

Singapore

Sur place

SGD 120 000 - 180 000

Plein temps

14 jours+

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Résumé du poste

Seatrium Limited is seeking an AI Engineer to develop and optimize machine learning models for complex business challenges. You will design and deploy algorithms to enhance AI capabilities and system performance, while collaborating with data scientists, engineers, and stakeholders.

You will design, integrate, and maintain NLP systems for AI-powered applications, evaluate emerging AI technologies, and ensure models meet accuracy and reliability targets in production environments.

Qualifications

  • Bachelor’s or Master’s degree in CS, AI, data science, or related field.
  • 2–3 years of experience in AI engineering, ML or DL.
  • Hands-on experience deploying ML models into production.
  • Strong knowledge of TF, PyTorch, Keras, Scikit-learn; cloud experience.

Responsabilités

  • Develop, implement, and optimize AI models for business problems.
  • Design and deploy ML algorithms to enhance AI capabilities and system performance.
  • Collaborate with data scientists, engineers, and stakeholders to improve model accuracy.
  • Design, integrate, and maintain NLP systems for AI-powered apps.
  • Test, validate, and monitor models for real-world performance.

Connaissances

React.js
Node.js
JavaScript
HTML
CSS

Formation

Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or related field

Outils

TensorFlow
PyTorch
Keras
Scikit-learn
AWS
Azure
REST APIs

Description du poste

Seatrium Limited is seeking an AI Engineer to develop and optimize machine learning models for complex business challenges. You will design and deploy algorithms to enhance AI capabilities and system performance, while collaborating with data scientists, engineers, and stakeholders.

You will design, integrate, and maintain NLP systems for AI-powered applications, evaluate emerging AI technologies, and ensure models meet accuracy and reliability targets in production environments.

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