Ai Engineer

PHOENIX SOLUTIONS (S) PTE. LTD.

Geylang, Singapore
Sgd 9,000 - 13,000 / monthly pm
On-site
Python programming for production code
Docker containerization and kubernetes orchestration
Mlflow or similar mlops tools
PHOENIX SOLUTIONS (S) PTE. LTD. is seeking an AI Engineer to design, develop, and deploy machine learning solutions, with a focus on operationalizing models and building CI/CD pipelines. The ideal candidate should possess strong Python programming skills, experience with LLMs, and familiarity with containerization and orchestration tools like Docker and Kubernetes

Job Summary

  • Design, develop and deploy machine learning solutions and services including end-to-end pipelines from data ingestion to model serving.
  • Operationalize large language models, embeddings, and multi-agent systems in real-world applications while managing the model lifecycle and promotion workflows.
  • Collaborate with data scientists, infrastructure teams, and other stakeholders to integrate machine learning solutions into existing systems and maintain CI/CD pipelines.

Matching Summary

Match Score: 85

PHOENIX SOLUTIONS (S) PTE. LTD. is seeking an AI Engineer to design, develop, and deploy machine learning solutions, with a focus on operationalizing models and building CI/CD pipelines. The ideal candidate should possess strong Python programming skills, experience with LLMs, and familiarity with containerization and orchestration tools like Docker and Kubernetes.

Salary

SGD 9,000 - 13,000 / Monthly

Skills & Requirements

Must-have

  • Python programming for production code
  • Docker containerization and Kubernetes orchestration
  • MLflow or similar MLOps tools
  • Experience with Large Language Models
  • CI/CD pipelines for ML models
  • Model lifecycle and deployment management

Nice-to-have

  • Understanding of GPU architecture and cloud compute
  • Collaboration with cross-functional teams
  • Code reviews and debugging skills
  • Knowledge of AI agents and agentic workflows
  • Data preprocessing and feature engineering

Key Requirements

  • Bachelor's or master’s degree in relevant field
  • Proven experience with machine learning or data science
  • Hands-on experience with MLflow or similar tools
  • Experience with Docker and Kubernetes
  • Experience working with LLMs
  • Hands-on CI/CD pipeline experience

Work Rights

Not specified

Tailored Resume

Cover Letter