Machine Learning Engineer, Vulcan

About the role

We are looking for a talented Machine Learning Engineer to join our Product Core Engineering team. You will be responsible for building and optimizing machine learning workflows that directly power our AI-driven products. This role focuses on the full lifecycle of model development - from training and fine-tuning to deployment and monitoring - ensuring robust and efficient ML systems at scale. Why Join Us? Product Impact: Your work will be directly embedded in our core AI products, shaping user experience and product capabilities. Engineering Excellence: Be part of a team that values high-quality engineering, reproducibility, and scalability. Innovation: Opportunity to experiment with cutting-edge ML and GenAI technologies in production settings. Collaboration: Work alongside backend, platform, and product teams in a highly collaborative environment. Competitive Package: Receive attractive compensation and benefits aligned with your skills and performance.

Responsibilities

• Model Development: Design and implement training processes for machine learning classifiers and generative models.
• Fine-tuning & Prompting: Adapt pre-trained models to specific product needs through fine-tuning, prompt engineering, and parameter optimization.
• Hyperparameter Management: Configure and tune hyperparameters to balance accuracy, robustness, and performance.
• Pipeline Engineering: Build scalable training and evaluation pipelines to support continuous experimentation.
• Integration: Collaborate with backend and product engineers to deploy models into production systems.
• Monitoring & Maintenance: Establish monitoring metrics and retraining strategies to maintain model performance in dynamic environments.

Requirements

• Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field.
• Proven experience in training classifiers and fine-tuning transformer-based models.
• Strong understanding of tokenization techniques, embedding models, and vector representations.
• Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.
• Familiarity with hyperparameter tuning and model configuration best practices.
• Experience working with large-scale datasets and building reproducible ML pipelines.
• Fluent in Mandarin; proficiency in English is an advantage.
• Knowledge of cloud platforms (AWS, Azure, GCP) and containerized deployment (Docker, Kubernetes).
• Experience with LLM prompting and fine-tuning is a plus.
• Basic understanding of data engineering practices (ETL, data validation, feature engineering).
• Exposure to AI safety, security, or bias mitigation techniques is an advantage.
• Other Benefits
• Work Life Balance is a must
• 15 days annual leaves (pro-rata for partial month at first year)
• 5 days full-pay sick leaves, 3 days menstrual leaves
• Health check subsidy
• Ergonomic-design chair and fully-equipped devices for work
• Hybrid remote work and flexible working hour.
• Grow together & keep learning
• Conferences & external subsidy
• Learning clubs to share technical skill (e.g: Frontend/Backend tech sharing, Blockchain...etc)
• Work Hard, Play even Harder
• Various entertainment & sports clubs, attend basketball clubs today, and play board game tomorrow!
• Snacks & beverage to refill your energy anytime

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