The AI/ML Software Engineer position is based in Malaysia with a hybrid work arrangement that includes both remote and in-office collaboration at the Kuala Lumpur HQ.
The role involves building AI systems that simplify, smarten, and make financial services more inclusive for millions of people across Southeast Asia.
Responsibilities include defining machine learning goals, building and deploying models for personalization and automation, owning data preprocessing and model evaluation, developing scalable ML pipelines, integrating ML outputs into applications, and staying updated on AI/ML research.
The position emphasizes direct impact on user experience, automation, and platform intelligence, with opportunities for fast growth in a flat, execution-driven team.
Requirements:
A Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field is required.
Candidates should have 2 to 4 years of experience in AI/ML engineering or backend software development.
Strong Python programming skills and familiarity with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn are necessary.
A solid understanding of the ML lifecycle, from data wrangling to model deployment, is essential.
Familiarity with deploying models into real-world systems or APIs is required.
Experience using tools like Jupyter, Google Colab, or cloud-based ML platforms is expected.
Strong analytical thinking, debugging, and communication skills are important.
Candidates must be based in Malaysia and able to work in a hybrid setup from PJ HQ.
Benefits:
The position offers a competitive salary along with performance-based bonuses.
Employees enjoy hybrid work flexibility, allowing for remote work and in-person collaboration at the PJ HQ.
There is high ownership and visibility in the role, with the opportunity for work to reach millions of users.
The company promotes rapid learning and growth in a mission-driven environment.
A flat organizational structure ensures that employee voices are heard and ideas are valued.
Employees gain cross-border exposure to regional product development.
