BJAK is hiring an AI Software Engineer (Founding AI Software Engineer) to develop intelligent systems that power personalized recommendations, fraud detection, automation, and search. Your work will make financial services more accessible across Asia. You will work remotely from Korea, collaborating closely with teams across Southeast Asia to define ML goals, build and deploy models, and manage the full ML lifecycle.

What You'll Do

Work with product, data, and engineering teams to define ML goals and technical strategies.
Design, build, and deploy machine learning models for personalization, automation, and insight generation.
Manage the ML lifecycle: data preprocessing, feature engineering, model training, evaluation, and deployment.
Build scalable ML infrastructure and deployment pipelines.
Integrate ML outputs into user-facing products and backend systems.
Stay current with AI/ML trends and apply relevant innovations into the stack.
Contribute to debugging, testing, and optimization of production ML systems.

What We're Looking For

Bachelor’s degree in Computer Science, Data Science, Engineering, or a related technical field.
2 - 4 years of experience in machine learning or backend software development.
Strong Python skills, with experience using frameworks like TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of ML workflows: data cleaning, model development, tuning, evaluation.
Familiar with model deployment, API development, or real-world ML integration.
Experience with tools like Google Colab, Jupyter, and cloud ML platforms.
Strong analytical, problem-solving, and communication skills.
Must be based in Korea and open to remote collaboration across time zones.

Nice to Have

Experience with NLP, computer vision, or recommendation systems.
Familiarity with cloud services (e.g., AWS, GCP, Azure).
Exposure to Docker, Git, or CI/CD tools.
Background working in a high-growth startup or agile product environment.

Technical Stack

Python, TensorFlow, PyTorch, Scikit-learn
Google Colab, Jupyter
Cloud ML platforms, AWS, GCP, Azure
Docker, Git, CI/CD tools

Team & Environment

Fast-paced, flat team structure. Mission-driven team. Lean, high-impact engineering environment. Team-first, humble, and helpful attitude. Emphasis on learning, sharing, and growth.