Machine Learning Engineer, Vulcan
AIFT Open · verified Oct 22, 2026 At a glance
Mid-level Machine Learning Engineering role at AIFT. Taipei.
Pay not stated Machine Learning Engineer salary
aimlroles summary, based on the employer's posting.
What you'll do
- Build training methods for classifiers and generative models, then tailor pre-trained models with fine-tuning and prompt design
- Adjust model parameters to balance accuracy, reliability and performance, and build scalable training and evaluation pipelines
- Coordinate with backend and product engineers to put models into production systems
- Set performance measures and retraining plans to keep models working as conditions shift
What you bring
- A bachelor’s or master’s degree in computer science, machine learning, data science or a related area
- Practical experience training classifiers and adapting transformer models, plus work with large datasets and repeatable ML pipelines
- A solid grasp of tokenization, embedding models and vector representations
- Python skills and experience with PyTorch, TensorFlow or Hugging Face Transformers
- You can work fluently in Mandarin
Who this fits
This mid-level role suits an engineer with experience spanning model development, production integration and ongoing performance monitoring. The role is based in Taipei and offers hybrid remote work and flexible hours.
From the employer
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.
Key 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.
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.
- Fluent in Mandarin; proficiency in English is an advantage.
Desired Skills
- 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
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, 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