AI Engineer
- Salary: Up to SGD 7,000 per month
- Contract Duration: 24 Months
- Location: Singapore
We are looking for an AI Engineer who thrives on solving complex engineering challenges—spanning backend development, AI inference optimisation, GPU infrastructure, and secure model deployment. If you enjoy working at the intersection of AI, DevOps, and MLOps, this role offers the opportunity to make a real impact.
What You'll Do:
AI Product Development & Backend Engineering
- Design and build scalable backend API services to power AI functionalities such as OCR, document parsing, and embedding-based applications.
- Deploy and manage large-scale LLMs (e.g., LLaMA, Mistral, GPT-based models) using containerized environments like Kubernetes / Red Hat OpenShift and vLLM.
- Integrate AI/ML models into RESTful or gRPC API endpoints to support enterprise use cases.
Model Deployment & MLOps
- Package, version, document, and deploy AI/ML models and services using MLflow, Kubeflow, or enterprise AI platforms (e.g., Dataiku).
- Drive high-reliability deployment pipelines and apply best practices in MLOps and model lifecycle management.
Inference Optimization
- Optimize performance through quantization, tensor parallelism, ONNX Runtime, TensorRT, and DeepSpeed.
- Implement dynamic batching and request multiplexing for low-latency, high-throughput inference.
- Profile and monitor inference workloads to eliminate bottlenecks and boost system efficiency.
AI Infrastructure Engineering
- Architect and maintain on-premise GPU/accelerator infrastructure for training and inference.
- Manage GPU job scheduling efficiently using Red Hat OpenShift.
Security, Compliance & Governance
- Embed security into the entire AI deployment lifecycle—including model validation, image signing, and runtime protection.
- Ensure compliance with enterprise security standards such as NIST and ISO 27001.
- Work closely with security teams to perform threat modelling and secure deployment assessments.
What You Bring:
- Bachelor's or Master's in Computer Science, Mathematics, Statistics, or related fields.
- 5+ years of experience in DevOps or MLOps, with at least 2 years focusing on AI/ML systems.
- Hands-on experience deploying and optimizing LLMs or transformer models in production.
- Strong proficiency with container technologies (preferably Red Hat OCP).
- Solid scripting and automation skills (Python, Bash).
- Good understanding of inference optimisation techniques (quantization, batching, parallelism).
- Strong knowledge of GPU infrastructure and performance tuning.
- Familiarity with secure software development and DevSecOps practices.
Why Join Us
- Build and deploy state-of-the-art AI systems used at enterprise scale.
- Work with a talented, high-impact engineering team on mission-critical AI initiatives.
- Gain hands-on experience with cutting-edge LLM technologies and advanced AI infrastructure.
- Contribute directly to shaping the organisation's AI ecosystem and future capabilities.
We'd love to hear from you! You may also reach out to Lovina (Staffing Specialist from BGC Group) at [Confidential Information] for more info.
