Technical Lead, Machine Learning
RemoteChina
Job Summary
Own end-to-end ML system execution, including 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 while architecting scalable inference systems that balance latency, cost, and reliability. Design data systems for high-quality synthetic and real-world training data and implement evaluation pipelines covering performance, robustness, safety, and bias. Collaborate with application engineering to integrate ML systems into backend, mobile, and desktop products, making pragmatic trade-offs to ship improvements quickly under real production constraints.
Required Qualifications
- Python
- PyTorch / JAX
- GPU-based training and inference system
- You have built or shipped real ML systems used by people, not just demos
- You are comfortable working with large models and understanding their failure modes
- You write strong, production-grade code and care about system correctness
- You are self-directed, pragmatic, and take full ownership of outcomes
- You communicate clearly and collaborate well in small, high-trust teams
- You are able to bring structure, exercise judgment, and execute independently
Desired Qualifications
- You have experience with LoRA, QLoRA, SFT, DPO, and distillation
- You have experience architecting and operating scalable inference systems
- You have experience designing and maintaining data systems for high-quality synthetic and real-world training data
- You have experience implementing evaluation pipelines covering performance, robustness, safety, and bias
- You have experience with GPU optimization, memory efficiency, latency reduction, and scaling policies
- You have experience collaborating closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products
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