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Machine Learning Engineer

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Onsite

Machine Learning Engineer

Base Camp Recruitment Pte Ltd

Machine Learning Engineer

Skills

Google Cloud PlatformSQL QueriesDockerPythonData SciencePyTorchTensorFlowMachine LearningAIAWSKubernetesBasecampApache AirflowAzure

1 month ago

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Important information


Contract type:

Permanent, Freelance / Contract

Work mode:

Onsite

Published on:

11 September 2026

What they need


Job title:

Machine Learning Engineer

Job type:

Contract

Emp type:

Full-time

Location:

Quarry Bay

Job published:

08-09-2026

Job ID:

43393

Contact name:

Lloyd Moorthy

Contact email:

[email protected]

Job Description

Machine Learning Engineer

Location: Hong Kong

Contract: 1-Year Contract | Highly Renewable

About the Role

We are seeking a Machine Learning Engineer on behalf of our client to design, develop and deploy production-grade ML and AI solutions. You will work across the full ML lifecycle, from model development and experimentation through to deployment, monitoring and optimization.

Key Responsibilities

  • Design, develop and deploy machine learning models into production.
  • Perform data preprocessing, feature engineering, model training and evaluation.
  • Build and maintain ML pipelines and MLOps workflows.
  • Develop scalable model-serving APIs and inference solutions.
  • Deploy ML applications using Docker/Kubernetes and cloud platforms.
  • Develop Generative AI / LLM / RAG solutions.
  • Monitor model performance, data quality and model drift.
  • Collaborate with Data Scientists, Data Engineers, Software Engineers and business stakeholders.

Mandatory Skills & Experience

  • 4+ years of experience in Machine Learning / AI Engineering.
  • Strong Python programming skills.
  • Hands-on experience with PyTorch, TensorFlow or scikit-learn.
  • Proven experience deploying ML models into production.
  • Strong experience in MLOps, ML pipelines and model deployment.
  • Experience with Generative AI / LLM / RAG.
  • Experience with LangChain, LangGraph or similar AI frameworks.
  • Experience with Hugging Face or equivalent LLM/model libraries.
  • Experience with vector databases such as FAISS, Pinecone, Milvus or Qdrant.
  • Experience with Docker and Kubernetes.
  • Experience with at least one cloud platform: AWS, Azure or GCP.
  • Strong SQL and data processing experience.
  • Good understanding of Git, REST APIs and CI/CD.
  • Bachelor's degree in Computer Science, AI, Data Science, Engineering, Mathematics or related discipline.

Preferred

  • Experience with MLflow / Kubeflow.
  • Experience with Spark / Airflow.
  • Experience with GPU-based model training or inference.
  • Experience in banking, financial services or other enterprise environments.

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