AI Engineer: NLP, LLMs & AI Pipelines

BGC Group Pte Ltd; Singapore; Sur place; SGD 81 000 - 97 000; Plein temps

Résumé du poste

BGC Group Pte Ltd is seeking an AI Developer to design, build, and deploy AI/ML solutions for LLM chatbots, forecasting, NLP and OCR in Singapore. The role involves end-to-end AI/ML pipelines, API integrations, and enterprise-grade deployment.

You will collaborate with data scientists and engineers, implement AI/ML Ops practices, containerize models, and support CI/CD workflows to deliver reliable AI-enabled features for business use.

Qualifications

• Bachelor's or Master's degree in Computer Science, Mathematics, Statistics, or a related field.
• At least 2 years of AI/ML model development and deployment experience.
• Strong understanding of AI/ML Ops practices and tools.
• Proficiency in ML frameworks (TensorFlow, PyTorch, Hugging Face) and coding in Python/Node.JS/Java.
• Experience with DevSecOps and containerization (Docker/OpenShift).
• Knowledge of GPU architectures is a plus.

Responsabilités

• Collaborate across teams to develop AI/ML products for LLM chatbots, forecasting, NLP and OCR.
• Design, build, test scalable AI/ML pipelines from preprocessing to deployment.
• Integrate AI/ML products into apps via RESTful APIs and microservices.
• Containerise models and support CI/CD workflows with DevSecOps.
• Follow software engineering practices like code reviews and test-driven development.

Connaissances

AI/ML development

Python

Node.JS

Java

Prompt engineering

LLM

API integration

Distributed systems

MLOps

Team collaboration

Formation

Bachelor's or Master's in CS/Math/Statistics

Outils

Jira

Asana

Smartsheet

Elasticsearch

Vector databases

Semantic search

Docker

OpenShift

Description du poste

BGC Group Pte Ltd is seeking an AI Developer to design, build, and deploy AI/ML solutions for LLM chatbots, forecasting, NLP and OCR in Singapore. The role involves end-to-end AI/ML pipelines, API integrations, and enterprise-grade deployment.

You will collaborate with data scientists and engineers, implement AI/ML Ops practices, containerize models, and support CI/CD workflows to deliver reliable AI-enabled features for business use.