28 days ago
Singapore, SingaporeStaff+
Responsibilities
- Own end-to-end ML system execution including data pipelines and deployment.
- Fine-tune and adapt models using advanced methods like LoRA and distillation.
- Architect and operate scalable inference systems balancing latency and cost.
- Design and maintain data systems for high-quality training data.
- Implement evaluation pipelines for performance and safety in collaboration with research.
- Manage production deployment focusing on optimization and scaling.
- Collaborate with application engineering for seamless ML system integration.
- Make pragmatic trade-offs and ship improvements quickly under real constraints.
Requirements
- Experience building or shipping real ML systems used by end-users.
- Comfortable working with large models and understanding their failure modes.
- Strong production-grade coding skills with a focus on system correctness.
- Self-directed and pragmatic with full ownership of outcomes.
- Excellent communication and collaboration skills in small teams.