Machine Learning Engineer, Vulcan

<p><strong>About the role</strong>&nbsp;</p>

<p>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.</p>

<h4><strong>Why Join Us?</strong></h4>

<ul>

<li>Product Impact: Your work will be directly embedded in our core AI products, shaping user experience and product capabilities.</li>

<li>Engineering Excellence: Be part of a team that values high-quality engineering, reproducibility, and scalability.</li>

<li>Innovation: Opportunity to experiment with cutting-edge ML and GenAI technologies in production settings.</li>

<li>Collaboration: Work alongside backend, platform, and product teams in a highly collaborative environment.</li>

<li>Competitive Package: Receive attractive compensation and benefits aligned with your skills and performance.</li>

</ul>

<h4><strong>Key Responsibilities</strong></h4>

<ul>

<li>Model Development: Design and implement training processes for machine learning classifiers and generative models.</li>

<li>Fine-tuning &amp; Prompting: Adapt pre-trained models to specific product needs through fine-tuning, prompt engineering, and parameter optimization.</li>

<li>Hyperparameter Management: Configure and tune hyperparameters to balance accuracy, robustness, and performance.</li>

<li>Pipeline Engineering: Build scalable training and evaluation pipelines to support continuous experimentation.</li>

<li>Integration: Collaborate with backend and product engineers to deploy models into production systems.</li>

<li>Monitoring &amp; Maintenance: Establish monitoring metrics and retraining strategies to maintain model performance in dynamic environments.</li>

</ul>

<p><strong>Qualifications</strong></p>

<ul>

<li>Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, or a related field.</li>

<li>Proven experience in training classifiers and fine-tuning transformer-based models.</li>

<li>Strong understanding of tokenization techniques, embedding models, and vector representations.</li>

<li>Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, or Hugging Face Transformers.</li>

<li>Familiarity with hyperparameter tuning and model configuration best practices.</li>

<li>Experience working with large-scale datasets and building reproducible ML pipelines.</li>

<li>Fluent in Mandarin; proficiency in English is an advantage.</li>

</ul>

<h4><strong>Desired Skills</strong></h4>

<ul>

<li>Knowledge of cloud platforms (AWS, Azure, GCP) and containerized deployment (Docker, Kubernetes).</li>

<li>Experience with LLM prompting and fine-tuning is a plus.</li>

<li>Basic understanding of data engineering practices (ETL, data validation, feature engineering).</li>

<li>Exposure to AI safety, security, or bias mitigation techniques is an advantage.</li>

</ul>

<p>&nbsp;</p>

<h3><strong>Other Benefits</strong>&nbsp;</h3>

<p>To us, people are our greatest&nbsp;asset,&nbsp;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.&nbsp;</p>

<p><strong>Work Life Balance is a must&nbsp;</strong>&nbsp;</p>

<ul>

<li>15 days annual leaves (pro-rata for partial month at first year)&nbsp;</li>

<li>5 days full-pay sick leaves,&nbsp;3 days menstrual leaves&nbsp;</li>

<li>Health check subsidy&nbsp;</li>

<li>Ergonomic-design chair and&nbsp;fully-equipped&nbsp;devices for work</li>

<li>Hybrid remote work and flexible working hour.</li>

</ul>

<p><strong>Grow together &amp; keep learning</strong></p>

<ul>

<li>Conferences &amp; external subsidy&nbsp;</li>

<li>Learning clubs to share technical skill (e.g: Frontend/Backend tech sharing, Blockchain...etc)&nbsp;</li>

</ul>

<p><strong>Work Hard, Play even Harder</strong>&nbsp;</p>

<ul>

<li>Various entertainment &amp; sports clubs,&nbsp;attend basketball clubs today, and play board game tomorrow!&nbsp;</li>

<li>Snacks &amp; beverage&nbsp;to refill your&nbsp;energy anytime&nbsp;</li>

</ul>