Machine Learning Engineer

Build AI Systems That Make Finance Simpler, Smarter, and More Inclusive

At BJAK, we’re building the next generation of intelligent financial services across Southeast Asia. As a Machine Learning Engineer, you’ll develop and deploy models that power key features - from personalization and risk scoring to automation and fraud detection. Your work will have a direct and visible impact on millions of users.

This is a remote role based in Indonesia, working closely with our HQ in Malaysia and cross-functional teams across the region. You’ll join a fast-paced team where your ideas and execution shape real-world outcomes every day.

Why This Role Matters

• You’ll design and scale ML solutions that directly impact product experience and efficiency
• You’ll contribute to production-grade systems that support millions of users
• You’ll have the opportunity to work on a variety of use cases across data, product, and engineering
• You’ll grow quickly in a lean, collaborative team with regional impact
  
  

What You’ll Do

• Collaborate with product, data, and engineering teams to define ML goals and use cases
• Develop, train, and deploy machine learning models to power core features (e.g., recommendation, classification, ranking)
• Own the ML lifecycle from data preprocessing and feature engineering to model training, tuning, and evaluation
• Build and maintain scalable ML pipelines and infrastructure
• Integrate models into backend systems and user-facing applications
• Monitor performance and retrain models based on feedback and new data
• Stay current with advancements in AI/ML and apply them where relevant
• Contribute to debugging, testing, and optimization of ML systems in production
  
  

You’ll Thrive Here If You...

• Take ownership of outcomes and care deeply about impact
• Are self-driven and able to figure things out without rigid instructions
• Are excited to work in a dynamic, high-growth startup with shifting priorities
• Enjoy solving end-to-end technical problems, even outside your comfort zone
• Value collaboration, humility, and knowledge-sharing with teammates
• Thrive in ambiguous environments and enjoy bringing structure through action
  
  

Requirements

• Bachelor's or Master's degree in Computer Science, Data Science, or related technical field
• 2-4 years of experience in ML, AI, or backend software engineering
• Proficient in Python and experienced with ML frameworks like TensorFlow, PyTorch, or Scikit-learn
• Solid understanding of the ML pipeline: data wrangling, feature engineering, model development, evaluation, and deployment
• Experience deploying models into real-world environments via APIs or cloud platforms
• Familiar with tools like Jupyter, Google Colab, and version control (Git)
• Strong problem-solving and communication skills
• Must be based in Indonesia and open to remote collaboration with regional teams
  
  

Nice to Have

• Experience in NLP, recommender systems, or computer vision
• Familiarity with cloud platforms (AWS, GCP, or Azure)
• Exposure to containerization tools like Docker and CI/CD pipelines
• Experience working in a fast-paced or high-growth startup environment
  
  

What You’ll Get

• Competitive salary and performance-based bonuses
• Flexible remote work arrangement from anywhere in Indonesia
• High-impact work with real visibility across the organization
• Flat structure where your ideas and contributions are valued
• Exposure to regional product development and collaboration
• Fast-tracked personal and professional growth
  
  

About BJAK

BJAK is Southeast Asia’s largest digital insurance platform, helping millions of users access transparent and affordable financial protection. Headquartered in Malaysia with presence in Thailand, Taiwan, and Japan, we’re building AI-powered solutions that simplify complex financial services through automation, smart recommendations, and cutting-edge APIs. Join us in reshaping financial access across ASEAN.

Excited to apply machine learning to real-world challenges? Join BJAK and help us build smarter, fairer financial systems for all.