Machine Learning Engineer

Nexus Global Pty Limited; Hong Kong; On-site; HKD 420,000 - 720,000; Full time

Job summary

Nexus Global Pty Limited seeks a Machine Learning Engineer to design, develop and deploy ML solutions that support business objectives across data science and engineering teams.

You will build scalable pipelines, collaborate with stakeholders to translate requirements into AIML applications, and ensure production readiness with MLOps and monitoring practices.

Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, Engineering or Mathematics or related field.
• 3 years of experience in machine learning model development and deployment.
• Strong programming skills in Python.
• Experience with ML frameworks such as Scikit-learn, TensorFlow, PyTorch or XGBoost.

Responsibilities

• Develop, train and optimize machine learning and deep learning models.
• Design and implement end-to-end ML pipelines for data preparation, model training, deployment and monitoring.
• Collaborate with data engineers to build scalable data processing solutions.
• Deploy and maintain ML models in cloud and on-premises environments.
• Monitor model performance and implement continuous improvement processes.
• Document technical designs, methodologies and implementation details.

Skills

Python

Scikit-learn

TensorFlow

PyTorch

XGBoost

ML pipelines

MLOps

Cloud (Azure)

Cloud (AWS)

Cloud (GCP)

Data structures

Algorithms

Statistics

SQL

Education

Bachelor's or Master's degree in Computer Science/Data Science/Engineering/Mathematics

Tools

Docker

Kubernetes

CI/CD

Job description

We are seeking a Machine Learning Engineer to design develop and deploy machine learning solutions that support business objectives The successful candidate will work closely with data scientists data engineers and business stakeholders to build scalable AIML models and integrate them into production environments.

Responsibilities

• Develop train and optimize machine learning and deep learning models
• Design and implement end-to-end ML pipelines for data preparation model training deployment and monitoring
• Collaborate with data engineers to build scalable data processing solutions
• Deploy and maintain ML models in cloud and on-premises environments
• Monitor model performance and implement continuous improvement processes
• Conduct model evaluation testing and troubleshooting
• Collaborate with business and technical teams to translate requirements into AIML solutions
• Document technical designs methodologies and implementation details
  

Requirements

What we are looking for

• Bachelors or Masters degree in Computer Science Data Science Engineering Mathematics or a related discipline
• 3 years of experience in machine learning model development and deployment
• Strong programming skills in Python
• Experience with ML frameworks such as Scikitlearn TensorFlow PyTorch or XGBoost
• Experience building and maintaining ML pipelines and MLOps practices
• Familiarity with cloud platforms such as Azure AWS or GCP
• Strong understanding of data structures algorithms statistics and model evaluation techniques
• Experience working with SQL and large datasets

Preferred Skills

• Experience with Generative AI and Large Language Models LLMs
• Knowledge of Docker Kubernetes and CICD practices
• Experience with vector databases, RAG architectures and AI application development
• Exposure to financial services or regulated industries

Languages

Business-level proficiency in Mandarin, Cantonese, and English is mandatory.