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Open nowPosted 4 days ago

Senior AI Engineer - AI Agents / RAG / Fine-Tuning

MyCareersFuture94,028 open roles

Pay
SGD 8,000 – SGD 11,000 a month
Where
West, Singapore
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Your applicationOpen nowSenior AI Engineer - AI Agents / RAG / Fine-TuningMyCareersFuture · West, Singapore

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  2. 3.4%3 days
  3. 7.8%7 days
  4. 14.3%14 days
  5. 33.7%30 days
This job: posted 4 days ago

The posting

About the Role

We are looking for experienced AI Engineer with hands-on experience in AI agents, Retrieval-Augmented Generation (RAG), and model fine-tuning. In this role, you will design, build, and optimize intelligent systems that enhance automation, knowledge retrieval, and decision-making across our product ecosystem. You will collaborate closely with product, engineering, and data teams to deliver scalable, production-grade AI solutions.

Key Responsibilities

  • Design, develop, and deploy AI agent systems capable of task planning, tool usage, and autonomous workflow execution.
  • Build and optimize RAG pipelines, including document chunking, embeddings, vector search, and retrieval orchestration.
  • Fine-tune large language models (LLMs) using instruction tuning, supervised fine-tuning (SFT), or reinforcement learning from human feedback (RLHF).
  • Implement high-performance inference pipelines and monitor model performance in production. Collaborate with cross-functional teams to integrate AI services into products and internal platforms.

Basic Qualifications

  • Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field.
  • 4–6 years of hands-on experience in machine learning or NLP engineering roles.
  • Strong proficiency in Python and AI/ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face).
  • Proven experience in: Building and deploying AI agents (LangChain, AutoGen, OpenAI Assistants, etc.) Designing RAG pipelines with vector databases (e.g., Pinecone, FAISS, Weaviate, Milvus) Fine-tuning LLMs on custom datasets Solid understanding of NLP concepts, embeddings, prompt engineering, and model evaluation.
  • Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes) is a plus. Strong problem-solving skills, communication ability, and a passion for applied AI innovation.

Preferred Qualifications

  • Experience with multi-agent systems or agent frameworks.
  • Knowledge of distributed systems and GPU optimization.
  • Familiarity with MLOps tools (Weights & Biases, MLflow, Ray, etc.).
  • Background in dataset curation and synthetic data generation.
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