AI/ML Engineer

PERCEPT SOLUTIONS PTE. LTD.; Singapore; On-site; SGD 90,000 - 150,000; Full time

Job summary

PERCEPT SOLUTIONS PTE. LTD. is seeking an AI/ML Engineer to design, develop, and deliver AI-powered enterprise solutions, including Agentic AI platforms, RAG, and knowledge management.

You will build production-ready services, integrate with enterprise data sources, containerise with Docker/Kubernetes/OpenShift, and implement CI/CD. Strong Python/SQL, ML frameworks, and prompt engineering are required.

Qualifications

• Hands-on proficiency in Python and SQL.
• Experience developing and integrating REST APIs.
• Practical experience with ML libraries and tools (Scikit-learn, XGBoost/LightGBM, TensorFlow or PyTorch).
• Experience building RAG solutions, vector search, and LLM applications.

Responsibilities

• Design AI agents and RAG solutions for enterprise use cases.
• Integrate AI services with enterprise data sources and applications.
• Containerise and deploy solutions using Docker, Kubernetes, and OpenShift (OCP).
• Develop production-ready REST APIs in Python and maintain CI/CD pipelines.
• Evaluate model performance and ensure reliability with monitoring.

Skills

Python

SQL

REST APIs

Scikit-learn

XGBoost/LightGBM

TensorFlow

PyTorch

Agentic AI

Prompt engineering

Memory & reasoning

Vector search

Dify

LLM apps

Tools

Docker

Kubernetes

OpenShift (OCP)

Git

CI/CD pipelines

Job description

We are seeking an AI/ML Engineer to design, develop, and deliver AI-powered enterprise solutions. The role covers Agentic AI platforms, Retrieval-Augmented Generation (RAG), recommendation engines, predictive analytics, workflow automation, and enterprise knowledge management. The successful candidate will combine software engineering, machine learning, and Generative AI expertise to build reliable, production-ready services integrated with enterprise systems.

Key Responsibilities:

Generative AI & Agent Development:

• Develop AI agents using modern Agentic AI frameworks and Dify.
• Build and optimise RAG solutions, including document ingestion, retrieval, vector search, and response generation.
• Design agent orchestration and tool-calling workflows to support enterprise use cases.
• Implement prompt engineering, agent memory, reflection, and evaluation capabilities.
• Develop AI-powered workflow automation and enterprise knowledge management solutions.

Machine Learning & Predictive Analytics:

• Develop machine learning models for recommendation systems, classification, ranking, and predictive analytics.
• Prepare and analyse data, engineer features, and evaluate model performance.
• Train and optimise models using Scikit-learn, XGBoost or LightGBM, and TensorFlow or PyTorch.

Engineering, Integration & Deployment:

• Build production-ready AI services and REST APIs using Python.
• Integrate AI solutions with enterprise data sources, repositories, and applications.
• Containerise and deploy solutions using Docker, Kubernetes, and OpenShift Container Platform (OCP).
• Implement and maintain CI/CD pipelines and manage source code using Git.

Monitoring & Evaluation:

• Implement monitoring, observability, and model evaluation frameworks.
• Assess retrieval quality, response accuracy, model performance, and service reliability.
• Troubleshoot issues and improve solution performance, scalability, and maintainability.
• Maintain technical documentation covering architecture, integrations, deployment, and operations.

Mandatory Requirements:

Programming & Integration:

• Hands-on proficiency in Python and SQL.
• Experience developing and integrating REST APIs.

Machine Learning:

• Practical experience with Scikit-learn.
• Experience with XGBoost or LightGBM.
• Experience with TensorFlow or PyTorch.
• Ability to develop and evaluate models for recommendation, classification, ranking, or predictive analytics.

Generative AI:

• Hands-on experience building RAG solutions and implementing vector search.
• Experience developing LLM applications.
• Practical experience using Dify.
• Experience developing agents using Agentic AI frameworks.
• Understanding of agent orchestration, tool calling, prompt engineering, memory, reflection, and evaluation.

Cloud & DevOps:

• Hands-on experience with OpenShift Container Platform (OCP), Docker, and Kubernetes.
• Experience implementing or maintaining CI/CD pipelines.
• Proficiency in Git and collaborative development workflows.

EA Licence No.:18S9405 / EA Reg. No.:R1330864