Job Title: AI / Machine Learning Engineer

Location: Hongkong 

Job Type: Full-time

About the Opportunity

Our client is seeking a talented AI/Machine Learning Engineer to join their innovative team. This role is at the center of their strategy, focused on designing, developing, and deploying sophisticated machine learning models and AI algorithms to solve complex business challenges.

Key Responsibilities

• Model Development: Design, develop, and implement advanced machine learning and deep learning models.
• Data Analysis: Conduct in-depth analysis of large-scale datasets to extract meaningful insights that inform and guide model development.
• Model Lifecycle Management: Take full ownership of the model lifecycle: train, validate, and fine-tune AI models to ensure exceptional robustness, accuracy, and performance.
• Experimentation: Develop prototypes and run experiments to benchmark different AI approaches and algorithms.
• Deployment & MLOps: Deploy AI solutions into production environments, integrate them with existing systems, and monitor their ongoing performance, making adjustments as needed.
• Troubleshooting: Act as the technical expert to troubleshoot and resolve complex issues related to production AI systems and models.
• Collaboration & Communication: Work closely with data engineers, software developers, and product managers. Document all workflows, models, and algorithms, and present findings clearly to both technical and non-technical stakeholders.

Required Qualifications & Skills

• Education: Bachelor’s degree or higher in Computer Science, Mathematics, Data Science, or a related field (advanced degrees are a plus).
• Production Experience: Demonstrable, hands-on experience building, deploying, and maintaining machine learning solutions in a production environment.
• Programming: Strong programming skills in Python, R, Java, or Scala.
• ML Frameworks: Deep knowledge of common ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras, scikit-learn).
• Fundamentals: Expertise in statistics, mathematics, and algorithms relevant to machine learning.
• Data Skills: Proven experience with data preprocessing, feature engineering, and model evaluation techniques.
• Specific Knowledge: Knowledge of Natural Language Processing (NLP). Experience with Microsoft's Semantic Kernel (C#) is a significant asset.
• Cloud Platforms: Familiarity with cloud platforms and tools for model deployment (e.g., AWS SageMaker, Lambda, or equivalents).
• Soft Skills: Strong collaborative and communication skills, with the ability to thrive in a multi-disciplinary team.

Preferred Qualifications (Nice-to-Have)

• Experience with Large Language Models (LLMs) such as GPT, BERT, or other Transformer-based architectures.
• A background in reinforcement learning, predictive analytics, or recommendation systems.
• Knowledge of CI/CD best practices and DevOps for ML (MLOps).
• Prior experience in leading AI projects or mentoring junior team members.

How to Apply

Interested candidates are invited to submit their resume, detailing their experience in deploying and maintaining production-level machine learning models.