Machine Learning Engineer

FPT Asia Pacific; Singapore; On-site; SGD 70,000 - 120,000; Full time

Job summary

A leading tech company in Singapore is looking for a Machine Learning Engineer to prototype and evaluate AI technologies for airport applications. Candidates should have a degree in Computer Science or related fields and 2-5 years of experience in ML development. The role involves working with LLMs, fine-tuning models, and using cloud platforms for deployment. Familiarity with Python and tools such as LangChain and AWS is essential. This position offers opportunities for hands-on prototyping and experimentation.

Qualifications

• 2-5 years of experience in ML/GenAI development or applied research.
• Hands-on experience with LLM APIs, LangChain, or LlamaIndex.
• Comfortable with rapid prototyping, experimentation, and iterative design.

Responsibilities

• Prototype and evaluate foundation and multimodal models.
• Fine-tune or adapt models using LoRA and PEFT techniques.
• Explore agentic AI tools to automate operational tasks.
• Document and share results, experiments, and learnings.

Skills

Python

Machine Learning Development

Prototyping

PyTorch

Transformers

Education

Bachelors or Masters degree in Computer Science, Machine Learning, or related fields

Tools

AWS

GCP

Docker

LangChain

Job description

About the job C01 - Machine Learning Engineer

About the Role

• We are seeking a Machine Learning Engineer to help prototype, evaluate, and operationalize emerging AI technologies for airport use cases.
• You will work hands‑on with LLMs, RAG pipelines, and AI agents, helping the team rapidly test hypotheses, build proofs of concept (PoCs), and deploy pilot systems in real operational contexts.

Key Responsibilities

• Prototype and evaluate foundation and multimodal models (e.g., GPT-4/5, Claude, Gemini, Llama 3, Mistral).
• Fine‑tune or adapt models using LoRA and PEFT techniques for airport‑specific data.
• Explore agentic AI tools (e.g., LangChain, AutoGen, CrewAI, LangGraph) to automate operational tasks.
• Build lightweight GenAI microservices with Python, FastAPI, and Docker for PoC deployment.
• Work with cloud platforms (AWS, GCP) for rapid model hosting and experimentation.
• Collaborate with data scientists and operations teams to test solutions in real‑world settings.
• Document and share results, experiments, and learnings for future scalability.

Qualifications

• Bachelors or Masters degree in Computer Science, Machine Learning, or related fields.
• 2-5 years of experience in ML / GenAI development or applied research.
• Proficiency in Python, PyTorch, and Transformers.
• Hands‑on experience with LLM APIs, LangChain, or LlamaIndex.
• Hands‑on experience with cloud ML platforms (AWS Sagemaker, Bedrock, GCP Vertex AI).
• Comfortable with rapid prototyping, experimentation, and iterative design.

Nice-to-have:

• Exposure to multimodal or agentic AI systems.
• Understanding of prompt design, evaluation metrics, or hallucination detection.