Key skills
MLCommunicationCollaboration
About this role
Role Overview
- Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems.
- Design and maintain data systems for training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias.
- Own production deployment including GPU optimization and scaling policies.
Requirements
- Experience in building or shipping real ML systems used by people
- Comfortable working with large models and understanding their failure modes
- Strong production-grade code writing skills
- Self-directed and pragmatic
- Clear communication and collaboration in small teams
Benefits
- Competitive salary
- Flexible working arrangements
- Professional development opportunities
- Health insurance