Senior AI Engineer

USER EXPERIENCE RESEARCHERS PTE. LTD.; Singapore; On-site; SGD 120,000 - 190,000; Full time

Job summary

USER EXPERIENCE RESEARCHERS PTE. LTD. is seeking an AI Engineer to design, develop, and deploy AI-powered applications.

You will build LLM-based features, integrate AI models, and collaborate with software, data, and product teams to deliver scalable AI products. The role requires 5+ years' experience in AI/ML, strong Python, proficiency with LLM frameworks, and hands-on work with OpenAI/Azure OpenAI. You will develop RAG pipelines, deploy via REST APIs, and optimize inference costs in

Qualifications

• Bachelor's degree in Computer Science, AI, Data Science, or a related field.
• 5+ years of experience in AI, Machine Learning, or Generative AI development.
• Strong proficiency in Python.
• Experience with LLM frameworks (LangChain, LlamaIndex, or similar).
• Hands-on experience with OpenAI, Azure OpenAI, Claude, or open-source LLMs.
• Knowledge of RAG, embeddings, and vector databases (Pinecone, Milvus, FAISS, ChromaDB).
• Experience with PyTorch or TensorFlow.
• Familiarity with Docker, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).
• Good understanding of API development and system integration.

Responsibilities

• Design, develop, and deploy AI/ML applications for production environments.
• Build and integrate Large Language Model (LLM) solutions using APIs and open-source models.
• Develop RAG (Retrieval-Augmented Generation) pipelines with vector databases.
• Create and optimize prompts, AI agents, and workflow automation.
• Fine-tune and evaluate machine learning and generative AI models.
• Build scalable REST APIs and integrate AI services with existing applications.
• Monitor model performance, improve accuracy, and optimize inference costs.
• Collaborate with cross-functional teams to translate business requirements into AI solutions.

Skills

Python

LLM frameworks

OpenAI / Azure OpenAI

RAG pipelines

Embeddings / vector databases

PyTorch / TensorFlow

Docker / Git / CI/CD

Cloud platforms (AWS/Azure/GCP)

API development

NLP / CV / Speech AI

Multi-agent AI

Education

Bachelor's degree in Computer Science, AI, Data Science, or related field

Tools

LangChain / LlamaIndex

Pinecone / Milvus / FAISS / ChromaDB

Kubernetes

Kubeflow / MLflow / Weights & Biases

Job description

We are looking for an AI Engineer to design, develop, and deploy AI-powered applications and machine learning solutions. The role involves building LLM-based features, integrating AI models into production systems, and collaborating with software, data, and product teams to deliver scalable AI products.

Key Responsibilities

• Design, develop, and deploy AI/ML applications for production environments.

• Build and integrate Large Language Model (LLM) solutions using APIs and open-source models.

• Develop RAG (Retrieval-Augmented Generation) pipelines with vector databases.

• Create and optimize prompts, AI agents, and workflow automation.

• Fine-tune and evaluate machine learning and generative AI models.

• Build scalable REST APIs and integrate AI services with existing applications.

• Monitor model performance, improve accuracy, and optimize inference costs.

• Collaborate with cross-functional teams to translate business requirements into AI solutions.

Requirements

• Bachelor's degree in Computer Science, AI, Data Science, or a related field.

• 5+ years of experience in AI, Machine Learning, or Generative AI development.

• Strong proficiency in Python.

• Experience with LLM frameworks (LangChain, LlamaIndex, or similar).

• Hands-on experience with OpenAI, Azure OpenAI, Claude, or open-source LLMs.

• Knowledge of RAG, embeddings, and vector databases (Pinecone, Milvus, FAISS, ChromaDB).

• Experience with PyTorch or TensorFlow.

• Familiarity with Docker, Git, CI/CD, and cloud platforms (AWS, Azure, or GCP).

• Good understanding of API development and system integration.

Preferred Skills

• Experience with AI agents and multi-agent architectures.

• Knowledge of MLOps tools (MLflow, Weights & Biases, Kubeflow).

• Experience deploying models on Kubernetes or cloud-native environments.

• Understanding of NLP, computer vision, or speech AI is an advantage.