Machine Learning Engineer

  • Very competitive
  • Singapore
  • Permanent, Full time
  • Hacker Trail
  • 20 May 19

Temasek's newly formed Root Access team is seeking pioneers with the grit and passion to champion the end-to-end digital transformation of our company. The Root Access team stays as nimble as possible, relentlessly pursuing cutting edge technologies and best practices (Agile, Quality Engineering, Lean, Design Thinking etc.) in order to build high-quality products and high-performing teams. Temasek's strong commitment to digital transformation brings about tremendous opportunities for huge impact to the organization, the local ecosystem and even the world.

We are looking for a "10x multiplier" - an individual with an insatiable intellectual curiosity and a heart for people, and therefore able to dramatically amplify the team's effectiveness.

Responsibilities:

  • Responsible for ensuring that ML models and pipelines are deployed successfully into production
  • Design technical architecture for applications using ML models
  • Deploy applications to AWS' cloud leveraging on the full spectrum of the AWS cloud services
  • Automate model training, testing and deployment using Continuous Integration/Continuous Delivery (CI/CD)
  • Create and implement metrics to verify effectiveness and soundness of the ML model​

Job requirements:

  • At least 4 years of working experience in building production quality and large scale deployment of applications related to machine learning
  • Experience in working in cross-functional Agile teams that practise Continuous Integration/Continuous Delivery (CI/CD).
  • Degree in computer science, software engineering, information technology or having equivalent experience
  • Strong programming fundamentals in at least one object oriented programming language (Python, Java, Scala, C++ etc.)
  • Solid background in algorithms and data structures
  • Knowledge of mining complex data (including structure and unstructured), identifying patterns, and feature engineering
  • Familiarity with a variety of classic and modern machine learning techniques including deep learning, clustering, decision tree, classification, regression and neural networks.
  • Familiarity with automated deployment and release engineering processes
  • Experience in Software Engineering