Machine Learning Engineer
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Job Description
Role Overview:
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.
Requirements
Role Overview:
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.