4 hours ago
Seoul, Korea, SouthStaff+
Responsibilities
- Own end-to-end ML system execution across data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- Fine-tune and adapt models using LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems while balancing latency, cost, and reliability.
- Design and maintain synthetic and real-world training data systems.
- Implement evaluation pipelines for performance, robustness, safety, and bias in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate with application engineering to integrate ML systems into backend, mobile, and desktop products.
- Detect, debug, and resolve production issues quickly while shipping measurable and safe improvements.
Requirements
- Built or shipped real machine learning systems used by people rather than only demos.
- Comfortable working with large models and understanding their failure modes.
- Writes strong production-grade code and cares about system correctness.
- Self-directed, pragmatic, and willing to take full ownership of outcomes.
- Communicates clearly and collaborates effectively in small, high-trust teams.
Categories
About Bjak
Our mission is to develop technology based solutions to improve financial inclusion. We develop new & innovative platforms & services globally. For example, we are the first platform to simplify and digitise comprehensive life and medical insurance, supported by AI agent. BJAK is the largest insurance platform in Southeast Asia. If you enjoy building cutting edge platform-ecosystems that gives equal access to financial services to everyone at scale, join us.