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.

• 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.

• 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.

Qualifications

• 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.

• 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.

To us, people are our greatest asset, and we are more than happy to invest in employees We create a healthy work atmosphere and provide you with the tools and support for doing your job successfully. With a culture of flexibility and transparency, we believe there should be no barriers, and everyone's contributions matter. 

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, ) 

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