Senior AI & ML Systems Lead

Sapsf; Singapore; On-site; SGD 150,000 - 190,000; Full time

Job summary

Sapsf in Singapore invites applications for a Senior Technical Lead (ML Eng) to design, build, and scale AI solutions within a DevOps-driven environment. You will drive end-to-end ML lifecycles from concept to deployment and collaborate with cross-functional teams.

You will deploy ML systems with multi-agent and RAG capabilities, ensure reliability in production, and orchestrate LLMs while optimizing performance across the stack.

Qualifications

• Bachelor's or Master's in DS/CS/Math/Stats or related field.
• Strong Python programming with ML libraries and DL frameworks (TensorFlow or PyTorch).
• Proven experience with Large Language Models (LLMs).
• Understanding of AI agents, orchestrators, and reasoning patterns.

Responsibilities

• Develop, deploy, and optimize ML/AI solutions for complex business challenges.
• Create multi-agent systems and agent/tool-calling capabilities.
• Design and implement RAG systems grounding AI responses in enterprise data.
• Assess and integrate AI models (e.g. LLMs) ensuring performance and reliability.
• Optimize agentic workflows for production use cases.
• Test and optimize system prompts and few-shot examples for accuracy and safety.
• Evaluate ML/AI models with appropriate metrics and datasets.
• Collaborate with platform teams, data engineers, data scientists, and stakeholders.
• Participate in code reviews, testing, and debugging to ensure quality.

Skills

Problem solving

Communication

Task prioritization

Continuous learning

Attention to detail

Education

Bachelor's or Master's in Data Science, Computer Science, Mathematics, Statistics, or related field

Tools

Python

TensorFlow

PyTorch

LLMs

Job description

Sapsf in Singapore invites applications for a Senior Technical Lead (ML Eng) to design, build, and scale AI solutions within a DevOps-driven environment. You will drive end-to-end ML lifecycles from concept to deployment and collaborate with cross-functional teams.

You will deploy ML systems with multi-agent and RAG capabilities, ensure reliability in production, and orchestrate LLMs while optimizing performance across the stack.