# Machine Learning Engineer, Vulcan at AIFT

> Taiwan · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/greenhouse%3Aaift%3A5652688004 (read 2026-11-09).

## Facts (observed)

- Company: [AIFT](https://alderhq.app/companies/aift)
- Location text: Taipei; Taiwan Office
- Where it can be done from (inferred): Taiwan (evidence: "Location: Taipei; Taiwan Office")
- Posted: 2025-09-17 (418 days ago)
- First seen by alder: 2026-11-04 · last verified: 2026-11-07
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://job-boards.greenhouse.io/aift/jobs/5652688004
- Skills listed (inferred): Python, AWS, GCP, Azure, Kubernetes, Docker, PyTorch, TensorFlow, LLMs

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

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

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Aaift%3A5652688004 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.