
Machine Learning Engineer at Bjak. Remote Location: Petaling Jaya, Malaysia. 📍 Working arrangement: Malaysia (Hybrid — remote + in-office). 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 role is based in Malaysia, with a hybrid working arrangement that combines the flexibility of remote work with in-person collaboration at our HQ. You’ll work closely with cross-functional teams across engineering, product, and data to solve real-world challenges using machine learning.. Why This Role Matters. You’ll design and scale ML solutions that directly impact product experience and operational efficiency. You’ll contribute to production-grade systems that serve millions of users. You’ll work across multiple ML domains — from automation to personalization. You’ll grow fast in a lean, collaborative team that rewards ownership and initiative. What You’ll Do. Collaborate with product, data, and engineering teams to define ML goals and use cases. Develop, train, and deploy ML models for core features such as recommendation, classification, and ranking. Own the end-to-end ML lifecycle: data preprocessing, feature engineering, model training, tuning, evaluation, and monitoring. Build scalable ML pipelines and infrastructure. Integrate models into backend services and user-facing applications. Monitor model performance and iterate based on real-world feedback and data. Stay current on AI/ML research and industry trends. Support debugging, testing, and production optimization of ML systems. You’ll Thrive Here If You.... Take full ownership — you don’t just build features, you care deeply about the outcomes they drive. Are a self-starter who figures things out, even when the path isn’t clearly defined. Embrace the intensity and urgency of startup life — shifting priorities, tight timelines, and high expectations energize you. Are comfortable wearing multiple hats, switching contexts, and solving problems across the stack. Have a bias for action — you move fast, experiment, and learn from doing. Value humility, collaboration, and helping others level up. Thrive in ambiguity and bring clarity through execution, not endless discussion. Constantly seek to improve yourself, your work, and the team — feedback is fuel, not friction. Requirements. Bachelor’s or Master’s degree in Computer Science, Data Science, or related field. 2–4 years of experience in machine learning, AI, or backend software engineering. Proficient in Python with experience using frameworks such as TensorFlow, PyTorch, or Scikit-learn. Solid understanding of the ML lifecycle — from data wrangling to deployment. Experience deploying models into real-world environments (APIs, cloud, etc.). Familiar with tools like Jupyter, Google Colab, and Git. Strong analytical and communication skills. Based in Malaysia and able to work in a hybrid setup (KL HQ + remote). Nice to Have. Experience in NLP, recommender systems, or computer vision. Familiarity with cloud platforms like AWS, GCP, or Azure. Exposure to Docker, CI/CD, or MLOps tools. Previous experience in a startup or fast-growth tech company. What You’ll Get. Competitive salary and performance bonuses. Flexible hybrid working model (remote + in-office). High-impact work that reaches millions across Southeast Asia. Flat team structure — fast decision-making, high visibility. Rapid career development in a mission-driven company. Cross-functional exposure to regional product and data teams. About BJAK. BJAK. is Southeast Asia’s largest digital insurance platform. Headquartered in Malaysia, with operations in Thailand, Taiwan, and Japan, we help millions access affordable, transparent financial protection via . Bjak.com. . We use AI, APIs, and intelligent automation to simplify and democratize access to insurance and financial products.. If you’re excited to apply machine learning to real-world problems and want to grow in a fast-moving, purpose-driven team — we’d love to hear from you.