Job Description:

  • Collaborate with product managers and data scientists to conceptualise, research, and build high performance and scalable machine learning solutions
  • Develop infrastructure, tooling, and frameworks to streamline development and deployment of machine learning models
  • Apply domain knowledge in machine learning and software engineering to contribute to various projects, including but not limited to:
    • MLOps
    • ML model training platform
    • ML model serving

Minimum Requirements:

  • Bachelor's Degree in Computer Science or related technical discipline
  • In-depth understanding of computer science fundamentals including algorithms and data structures
  • Experience in one or more programming languages (Go, C++, Java, Python)
  • Experience in developing and deploying machine learning or other web backend services
  • Experience in common machine learning frameworks (numpy, scikit-learn, xgboost, Tensorflow, PyTorch)

Preferred Requirements:

  • Experience in building and optimising big data pipelines
  • Experience in distributed databases or systems (Hadoop, Spark, HBase)
  • Experience in Kubeflow or similar machine learning platforms
  • Experience in one or more model serving frameworks (Tensorflow Serving, TorchServe, TensorRT, NVIDIA Triton Inference Server)

Minimum Qualifications:

  • Bachelor's Degree, Master's Degree, or PhD in Computer Science or related technical discipline
  • Minimum 2 years of relevant working experience for candidates with Bachelor's or Master’s Degree
  • Experience with one or more programming languages including Python and Golang
  • Familiarity with Linux Operating Systems
  • Experience in developing and deploying live services

Preferred Qualifications:

  • Proficient in SQL, building ETL data pipelines, and managing features in data warehouse / data lake
  • Experience with distributed databases or distributed systems (Hadoop, Spark, HBase, Cassandra etc.
  • Experience administering infrastructure and services in production environment
  • Familiar with DevOps best practices
  • Familiar with Docker and Kubernetes
  • Experience deploying services in a multi-cloud environment
  • Experience with Kubeflow or similar Machine Learning platforms
  • Experience with common machine learning frameworks including scikit-learn, XGBoost, Tensorflow, or PyTorch
  • Experience with Tensorflow Serving / TensorRT / TensorRT Inference Server
  • Experience with front-end development frameworks and building admin console

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