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Open nowPosted today

AI Engineer

MyCareersFuture99,426 open roles

Pay
SGD 6,000 – SGD 10,000 a month
Where
Central, Singapore
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Your applicationOpen nowAI EngineerMyCareersFuture · Central, Singapore
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The clock on this job

Early applications get read.

8.2% of postings close within 7 days. Measured by our own scanner across the market. MyCareersFuture postings stay open a median of 4 days.

Share of postings closed within
  1. 1.8%1 day
  2. 3.8%3 days
  3. 8.2%7 days
  4. 15.2%14 days
  5. 34.2%30 days
This job: posted today

MyCareersFuture median: 4 days open

The posting

Job Title: AI Engineer

Job Description

We’re looking for an AI Engineer to design, build and deploy AI solutions that solve real business problems. You’ll work closely with product, data and engineering teams to take models from prototype to production, with a strong focus on large language models (LLMs) and applied machine learning.

Key Responsibilities

  • Design, develop and deploy AI/ML models and LLM-based applications into production
  • Build and maintain retrieval-augmented generation (RAG) pipelines, agents and prompt workflows
  • Fine-tune and evaluate models for accuracy, latency, cost and safety
  • Develop APIs and integrate AI capabilities into existing products and enterprise systems
  • Set up MLOps practices, including CI/CD, model monitoring, versioning and retraining
  • Prepare, clean and manage datasets for training and evaluation
  • Work with stakeholders to translate business requirements into technical solutions
  • Keep up with developments in AI and recommend new tools and approaches where they add value
  • Ensure solutions meet data privacy, security and responsible AI standards

Requirements

  • Degree in Computer Science, Engineering, Data Science or a related field
  • At least 3 years of experience in software engineering, machine learning or AI development
  • Strong programming skills in Python; experience with PyTorch, TensorFlow or similar frameworks
  • Hands-on experience with LLMs (e.g. OpenAI, Anthropic, open-source models) and frameworks such as LangChain or LlamaIndex
  • Experience with vector databases (e.g. Pinecone, Weaviate, pgvector) and embedding models
  • Experience deploying models on cloud platforms (AWS, Azure or GCP) using Docker and Kubernetes
  • Solid understanding of machine learning fundamentals, NLP and model evaluation
  • Familiarity with MLOps tools (e.g. MLflow, Kubeflow, SageMaker) is an advantage
  • Good communication skills and ability to explain technical concepts to non-technical stakeholders

Good to Have

  • Experience integrating AI with enterprise applications (SAP, Oracle, Salesforce, Workday)
  • Exposure to multi-agent systems or AI agent orchestration
  • Knowledge of AI governance frameworks, including Singapore’s Model AI Governance Framework
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