AI/ML Engineer

Singapore (Singapore)

Role Overview

We are seeking for our client an experienced AI/ML Engineer with strong expertise in Large Language Models (LLMs), Agentic AI, prompt engineering, model fine-tuning, Reinforcement Learning from Human Feedback (RLHF), Retrieval-Augmented Generation (RAG), and agent orchestration frameworks.

The ideal candidate will have hands-on experience building, fine-tuning, and optimizing AI agents using client's AI ecosystem, including Vertex AI, PaLM, and Gemini. This role requires a deep understanding of transformer architectures, prompt optimization techniques, model evaluation, and emerging agent communication protocols.

The successful candidate will collaborate with cross-functional teams to design, develop, evaluate, and deploy next-generation AI solutions for complex business use cases.

Key Responsibilities

• Design, develop, and optimize prompt engineering strategies for large language models.
• Build and curate high-quality datasets for Retrieval-Augmented Generation (RAG) and model fine-tuning.
• Fine-tune large language models using domain-specific datasets.
• Apply RLHF techniques to improve model accuracy and agent decision-making.
• Design, develop, and deploy AI agents using Vertex AI, PaLM, and Gemini.
• Collaborate with engineering teams to define agent architecture, orchestration strategies, and evaluation frameworks.
• Implement Agent-to-Agent (A2A) communication and orchestration mechanisms.
• Standardize agent interactions using the Model Context Protocol (MCP).
• Develop and maintain scalable machine learning pipelines.
• Evaluate model performance and implement continuous optimization strategies.
• Conduct experiments involving prompt tuning, chain-of-thought reasoning, and agent workflows.
• Stay current with the latest developments in generative AI, agent frameworks, and LLM optimization techniques.

Required Skills and Qualifications

AI/ML Expertise

• Minimum 3 years of experience in AI/ML engineering.
• Strong understanding of Large Language Models (LLMs).
• Experience with prompt engineering and prompt optimization.
• Hands-on experience with RAG architectures.
• Experience fine-tuning foundation models using domain-specific datasets.
• Practical experience applying RLHF techniques.
• Knowledge of transformer-based architectures.

Agentic AI Frameworks

Experience with:

• Agent Development Kit (ADK)
• Agentspace
• Agent-to-Agent (A2A) protocols
• Model Context Protocol (MCP)

Model Optimization Techniques

Knowledge of:

• LoRA (Low-Rank Adaptation)
• Quantization
• PEFT (Parameter-Efficient Fine-Tuning)
• Prompt tuning
• Chain-of-thought methodologies

Programming Skills

Strong programming experience in:

• Python
• TensorFlow
• JAX
• PyTorch

Language Requirement

• Fluent Chinese language skills are mandatory.
• Ability to communicate effectively with Chinese-speaking stakeholders and technical teams.

Primary Skills

• Prompt Engineering
• RAG Dataset Curation
• LLM Fine-Tuning
• RLHF
• Vertex AI
• PaLM
• Gemini
• Agent Architecture
• Agent Evaluation
• MCP
• A2A
• ADK
• Agentspace
• Python
• TensorFlow
• JAX
• PyTorch
• LoRA
• PEFT
• Quantization
• Prompt Tuning
• Chain-of-Thought Reasoning

Preferred Qualifications

• Experience building production-grade AI applications.
• Experience developing and deploying AI agents at scale.
• Exposure to enterprise AI implementations.
• Experience working in cloud-based machine learning environments.

If you are passionate about building next-generation AI solutions and have hands-on experience with LLMs and Agentic AI frameworks, we would love to hear from you.

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