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Machine Learning Engineer

Southeast Asia's largest digital insurance platform helping millions of users access transparent, affordable financial protection.
Machine Learning
Mid-Level Software Engineer
Hybrid
501 - 1,000 Employees
2+ years of experience
AI · Finance · Enterprise SaaS

Description For Machine Learning Engineer

BJAK, Southeast Asia's largest digital insurance platform, is seeking a talented Machine Learning Engineer to join their team in Taipei, Taiwan. This role offers a unique opportunity to build AI systems that make finance simpler, smarter, and more inclusive across Southeast Asia.

As a Machine Learning Engineer, you'll be at the forefront of developing and deploying critical ML models that power core features – from personalization and risk scoring to automation and fraud detection. Your work will directly impact millions of users across the region, making financial services more accessible and efficient.

The position operates on a hybrid work model, based in Taiwan while collaborating closely with the Malaysian headquarters and cross-functional teams across the region. You'll be part of a fast-moving, execution-driven team where ideas quickly transform into real-world solutions.

Key responsibilities include building and deploying various ML models, managing the complete ML lifecycle, developing scalable pipelines, and integrating solutions into production systems. You'll work closely with product managers, data scientists, and engineers to define goals and use cases, while continuously optimizing model performance based on real-world feedback.

The ideal candidate should have 2-4 years of ML, AI, or backend development experience, strong Python skills, and familiarity with major ML frameworks. You should be comfortable with end-to-end ML development, from data preprocessing to deployment, and have experience with cloud infrastructure and API integration.

BJAK offers a competitive package including performance bonuses, flexible work arrangements, and significant growth opportunities. With presence across Thailand, Taiwan, and Japan, this role provides excellent exposure to regional markets and the chance to impact financial services across Southeast Asia.

If you're passionate about applying ML to solve real-world problems, thrive in fast-paced environments, and want to be part of making financial services more accessible and fair, this role offers an exciting opportunity to make a meaningful impact while advancing your career in ML engineering.

Last updated 2 days ago

Responsibilities For Machine Learning Engineer

  • Collaborate with PMs, data scientists, and engineers to define ML goals and use cases
  • Build, train, and deploy models for recommendation, classification, ranking, and detection
  • Manage the ML lifecycle: data wrangling, feature engineering, training, evaluation, deployment
  • Develop scalable ML pipelines and backend services
  • Integrate models into production systems and user-facing applications
  • Analyze model performance and iterate based on feedback
  • Stay updated on AI/ML advancements and drive innovation
  • Contribute to debugging, testing, and performance optimization

Requirements For Machine Learning Engineer

Python
  • Bachelor's or Master's degree in CS, Data Science, or related technical field
  • 2–4 years of ML, AI, or backend development experience
  • Proficient in Python and familiar with ML frameworks like TensorFlow, PyTorch, Scikit-learn
  • Strong ML development skills: preprocessing, modeling, evaluation, deployment
  • Experience deploying models via APIs or cloud infra
  • Familiarity with Jupyter, Git, and collaborative coding tools
  • Excellent problem-solving, communication, and teamwork skills
  • Must be based in Taiwan and open to hybrid regional collaboration

Benefits For Machine Learning Engineer

  • Competitive salary and performance bonuses
  • Hybrid work setup – flexibility to work from home or office
  • High-impact role with visibility across product and leadership
  • Flat structure – your voice is heard, and your work is valued
  • Fast learning curve and technical growth opportunities
  • Regional collaboration across Southeast Asia

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