Machine Learning Engineer (Senior/Principal) - Model Training

Michael Page Singapore; Singapore; On-site; SGD 120,000 - 180,000; Full time

Benefits offered by this job

Competitive salary

Comprehensive benefits package

Job summary

Michael Page Singapore is recruiting for a role focused on building and optimizing large-scale ML and GenAI models in an enterprise setting. The candidate will develop AI agents and LLM-powered applications while improving GPU training and inference performance.

The position involves designing scalable ML pipelines, cloud-based AI solutions, and implementing CI/CD for ML deployments, with close collaboration with data scientists and engineering teams.

Qualifications

• Experience building ML/GenAI models at scale.
• Experience with distributed GPU training and inference.
• Experience implementing CI/CD for ML workloads.

Responsibilities

• Build and optimize large-scale ML and GenAI models.
• Develop AI agents and LLM-powered applications.
• Improve GPU training and inference performance.
• Design scalable ML pipelines and cloud-based AI solutions.
• Implement CI/CD and deployment frameworks.
• Collaborate with data scientists and engineering teams.

Skills

LLM infra stack

Large-scale ML training

GPU training optimization

CI/CD for ML

Tools

LangChain

LangGraph

LlamaIndex

DeepSpeed

TensorRT-LLM

Job description

• Own and drive end-to-end AI solutions in an enterprise environment
• Competitive salary and comprehensive benefits package.

About Our Client

Our client is a global technology leader that develops advanced computing, data, and intelligent systems solutions used worldwide. Known for its commitment to innovation, research excellence, and engineering expertise, the organization invests heavily in artificial intelligence, high-performance computing, and digital transformation initiatives to solve complex business and industrial challenges.

Job Description

• Build and optimize large-scale ML and GenAI models.
• Develop AI agents and LLM-powered applications.
• Improve GPU training and inference performance.
• Design scalable ML pipelines and cloud-based AI solutions.
• Implement CI/CD and deployment frameworks.
• Collaborate with data scientists and engineering teams.

The Successful Applicant

This role is ideal for someone who enjoys working across the full LLM infrastructure stack, including:

• Large-scale model training and fine-tuning (SFT, RLHF) - Hiring Priority
• Distributed GPU systems (DDP, FSDP, DeepSpeed, multi-node training)
• Inference optimization (vLLM, TensorRT-LLM)
• Good-to-Have: Agentic AI development using frameworks such as LangChain, LangGraph, and LlamaIndex

What\'s on Offer

• Competitive salary and bonus.
• Exposure to GenAI, Agentic AI, and large-scale AI systems.
• Opportunity to work with advanced GPU infrastructure.
• Strong career growth and learning opportunities.
• Collaborative and innovative engineering culture.