AI Engineer

ICUBE; Jakarta Pusat; On-site; IDR 500,000,000 - 850,000,000; Full time

Job summary

ICUBE in Jakarta is seeking a seasoned AI/ML Engineer to design and deploy production-grade systems, including computer vision pipelines and real-time inference services. You will work with LLMs, RAG architectures, vector databases like FAISS, Qdrant, and Azure AI Search, building scalable microservices with Docker/Kubernetes in a cloud environment.

A strong foundation in Python, ML tooling, and cloud platforms (GCP preferred; AWS/Azure welcome) is essential to transform proofs-of-concept into

Qualifications

• Proven experience deploying production-grade AI/ML systems, as reflected in organizational resumes (e.g., computer vision pipelines, real-time inference services).
• Hands-on experience with LLMs, RAG architecture, vector databases (FAISS, Qdrant, Azure AI Search).
• Solid understanding of software engineering fundamentals: API development, microservices, distributed systems.
• Experience with Docker and Kubernetes, widely used in production deployments across internal candidates.
• Proficiency with cloud platforms (GCP preferred; AWS/Azure also welcome).
• Strong grasp of CI/CD, automated testing, model lifecycle management, and observability.
• Familiarity with real-time processing (streaming, queues, event-driven architecture).

Skills

Python

Machine Learning

LLM experience

Real-time processing

Fast learner

Tools

Docker

Kubernetes

FAISS

Qdrant

Azure AI Search

GCP

AWS

Azure

LangChain

Job description

• Proven experience deploying production-grade AI/ML systems, as reflected in organizational resumes (e.g., computer vision pipelines, real-time inference services).
• Hands-on experience with LLMs, RAG architecture, vector databases (FAISS, Qdrant, Azure AI Search).
• Solid understanding of software engineering fundamentals: API development, microservices, distributed systems.
• Experience with Docker and Kubernetes, widely used in production deployments across internal candidates.
• Proficiency with cloud platforms (GCP preferred; AWS/Azure also welcome).
• Strong grasp of CI/CD, automated testing, model lifecycle management, and observability.
• Familiarity with real-time processing (streaming, queues, event-driven architecture).

Technical Skills

• Strong proficiency in Python + ML ecosystem (PyTorch, TensorFlow, scikit‑learn, Hugging Face, LangChain).
• Proven experience deploying production-grade AI/ML systems, as reflected in organizational resumes (e.g., computer vision pipelines, real-time inference services).
• Hands-on experience with LLMs, RAG architecture, vector databases (FAISS, Qdrant, Azure AI Search).
• Solid understanding of software engineering fundamentals: API development, microservices, distributed systems.
• Experience with Docker and Kubernetes, widely used in production deployments across internal candidates.
• Proficiency with cloud platforms (GCP preferred; AWS/Azure also welcome).
• Strong grasp of CI/CD, automated testing, model lifecycle management, and observability.
• Familiarity with real-time processing (streaming, queues, event-driven architecture).

Soft Skills

• Fast learner with ability to adopt new AI frameworks and technologies quickly.
• Strong problem-solving mindset with practical approach to converting POC into production systems.
• Clear communicator who can explain technical concepts to a variety of stakeholders.