Michael Page

Senior/Principal Machine Learning Engineer - Model Training

Michael Page

Singapore · Full Time

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Experience
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Salary
Openings
1
Posted
4 days ago
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In office
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Job description

About the Company

The client is a prominent global technology enterprise recognized for pioneering advancements in computing, data science, and intelligent systems. It emphasizes innovation, research excellence, and engineering prowess, focusing on artificial intelligence, high-performance computing, and digital transformation to address intricate industrial and business challenges.

Role Overview and Responsibilities

  • Lead and manage the complete lifecycle of AI solutions within an enterprise setting.
  • Design, build, and optimize extensive machine learning and generative AI models.
  • Develop AI agents and applications powered by large language models (LLM).
  • Enhance GPU training and inference efficiency and performance.
  • Architect scalable machine learning pipelines alongside cloud-based AI infrastructures.
  • Implement continuous integration/delivery (CI/CD) and deployment systems.
  • Collaborate closely with data scientists and engineering teams to deliver robust AI solutions.

Ideal Candidate Profile

  • Experience in large-scale model training and fine-tuning methods such as Supervised Fine Tuning (SFT) and Reinforcement Learning with Human Feedback (RLHF); this is a hiring priority.
  • Familiarity with distributed GPU training systems including Distributed Data Parallel (DDP), Fully Sharded Data Parallel (FSDP), DeepSpeed, and multi-node training techniques.
  • Expertise in optimizing inference speed and resource utilization with tools like vLLM and TensorRT-LLM.
  • Preferably experienced in developing agentic AI using frameworks such as LangChain, LangGraph, and LlamaIndex.

Compensation and Benefits

  • A competitive salary package complemented by performance-based bonuses.
  • Exposure to cutting-edge technologies, including Generative AI, Agentic AI, and enterprise-scale AI architectures.
  • Opportunities to work with advanced GPU infrastructure and to engage in substantial career development and learning.
  • A collaborative and innovative engineering culture fostering professional growth.

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