Senior AI/ML Engineer - Edge, MLOps & Generative AI

ST ENGINEERING ADVANCED NETWORKS & SENSORS PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ST Engineering Advanced Networks & Sensors is seeking a Senior AI/ML Engineer to design, build, and deploy production‑grade AI/ML solutions. You will work with product, software, data, and platform teams to translate complex needs into secure, reliable AI capabilities.

The role emphasizes MLOps, responsible AI governance, and scalable architectures, including LLM/RAG implementations, with opportunities to influence edge deployments and enterprise workflows.

Qualifications

• Minimum 5 years delivering AI/ML, data science, or intelligent software solutions in production environments.
• Strong Python and SQL skills with solid software engineering practices.
• Experience building Generative AI/LLM solutions, including embeddings, vector search, RAG, and evaluation.
• Knowledge of APIs, MLOps, CI/CD, containers, monitoring, and cloud/on‑prem deployments.
• Ability to work with cross‑functional teams and communicate complex concepts clearly.

Responsibilities

• Translate business needs into AI/ML solutions with clear objectives, success metrics, and delivery plans.
• Design, develop, fine‑tune, and optimize ML, deep learning, and Generative AI solutions.
• Build LLM applications using RAG, tool/function calling, structured outputs, and agentic workflows.
• Develop reusable AI components, standards, and frameworks to accelerate delivery.
• Collaborate with product, software, data, platform, cybersecurity, quality, and business teams to deliver outcomes.

Skills

Python

SQL

ML Frameworks

Generative AI / LLM

MLOps / CI-CD

Cloud / Edge Deployment

Tools

Docker

Kubernetes

APIs

LLM tooling

Job description

ST Engineering Advanced Networks & Sensors is seeking a Senior AI/ML Engineer to design, build, and deploy production‑grade AI/ML solutions. You will work with product, software, data, and platform teams to translate complex needs into secure, reliable AI capabilities.

The role emphasizes MLOps, responsible AI governance, and scalable architectures, including LLM/RAG implementations, with opportunities to influence edge deployments and enterprise workflows.