Technical Lead, ML Systems - Build Production-Ready AI

AI Chopping Block; Singapore; On-site; SGD 180,000 - 250,000; Full time

Job summary

AI Chopping Block in Singapore seeks a Technical Lead, Machine Learning, to own the execution layer of our intelligence. You will translate research direction into reliable, production-grade ML systems, shaping data pipelines, training workflows, deployment, and observability.

You’ll work across research, infrastructure, and product, optimize GPUs, latency, and memory, and collaborate with backend, mobile, and desktop teams to ship scalable solutions with real-world impact.

Qualifications

• Experience building and shipping real ML systems
• Ability to work with large models and understand failure modes
• Strong production-grade coding skills and system correctness
• Self-directed, pragmatic, and takes ownership of outcomes
• Clear communication and collaboration in small, high-trust teams

Responsibilities

• 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, balancing latency, cost, and reliability.
• Design and maintain data systems for high-quality synthetic and real-world training data.
• Implement evaluation pipelines covering 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.
• Make pragmatic trade-offs and ship improvements quickly, learning from real usage.

Skills

Python

PyTorch

JAX

LoRA

QLoRA

SFT

DPO

Distillation

Job description

AI Chopping Block in Singapore seeks a Technical Lead, Machine Learning, to own the execution layer of our intelligence. You will translate research direction into reliable, production-grade ML systems, shaping data pipelines, training workflows, deployment, and observability.

You’ll work across research, infrastructure, and product, optimize GPUs, latency, and memory, and collaborate with backend, mobile, and desktop teams to ship scalable solutions with real-world impact.