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4,147
Ai jobs in Singapore
AI/ML Engineer (DevOps | MLOps | LLM | 5000-7000 SGD | GOVT)
BGC GROUP PTE. LTD.
Singapore
On-site
SGD 80,000 - 100,000
19 days ago
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AI Automation Specialist
INFINITY FINANCIAL ADVISORY PTE. LTD.
Singapore
On-site
SGD 60,000 - 90,000
25 days ago
AI/CIO Engineer | 24-Month Contract | Salary Up to $7K
BGC GROUP PTE. LTD.
Singapore
On-site
SGD 90,000 - 120,000
28 days ago
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Income Insurance Limited
Singapore
On-site
SGD 70,000 - 100,000
28 days ago
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Flexxon
Singapore
On-site
SGD 80,000 - 120,000
19 days ago
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Singapore
On-site
SGD 60,000 - 80,000
20 days ago
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A*STAR RESEARCH ENTITIES
Singapore
On-site
SGD 70,000 - 120,000
20 days ago
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Fairygodboss
Singapore
On-site
SGD 120,000 - 160,000
22 days ago
Instructor - Generative AI
VERTICAL INSTITUTE PTE. LTD.
Singapore
On-site
SGD 20,000 - 60,000
28 days ago
Research Scientist (CFAR), IHPC
A*STAR RESEARCH ENTITIES
Singapore
On-site
SGD 80,000 - 110,000
28 days ago
AI/ML Engineer (DevOps | MLOps | LLM | 5000-7000 SGD | GOVT)
BGC GROUP PTE. LTD.
Singapore
On-site
SGD 80,000 - 100,000
Full time
19 days ago
Job summary
A technology specialist firm in Singapore is seeking an experienced AI/ML Engineer to develop and deploy AI products while managing AI infrastructure. Responsibilities include design and implementation of backend services, inference optimization, and ensuring compliance with security standards. Ideal candidates should have significant experience in DevOps and MLOps, with expertise in deploying LLMs and a solid understanding of security practices. The role offers a salary of 5000-7000 SGD plus bonuses.
Qualifications
- 5+ years in DevOps, MLOps, with 2+ years in AI/ML systems.
- Hands-on experience deploying and optimizing LLMs in production.
- Strong understanding of AI/MLOps practices and tools.
Responsibilities
- Design and develop backend API services for AI functionalities.
- Deploy and manage large-scale LLMs in containerized environments.
- Tune inference performance using model optimization techniques.
- Design and manage scalable GPU infrastructure for AI workloads.
Skills
DevOps practices
MLOps tools
Container technologies
Scripting skills
Inference optimization techniques
GPU infrastructure
Secure software development practices
Education
Bachelor’s or Master’s degree in Computer Science or related field
Tools
Redhat OCP
MLflow
Kubeflow
TensorRT
ONNX Runtime
DeepSpeed
Python
Bash
Job description
- Job Title: AI/ML Engineer (DevOps | MLOps | 5000-7000 SGD | GOVT)
- Duration: 24 months
- Location: Bukit Merah Central / Depot Rd
- Salary: 5000-7000 + AWS + Performance Bonus
- Eligibility: Only Singaporeans
Responsibilities
- Development and Deployment of AI products and AI-Driven Backend services:
- Design and develop backend API services for AI-powered functionalities that are reusable and scalable to support business use cases (e.g. OCR, document parsing, embedding model APIs)
- Deploy and manage large-scale LLMs (e.g., LLaMA, Mistral, GPT-based models) in containerized environments using tools like Kubernetes (Redhat OCP preferred) and vLLM and integrate into RESETful or gRPC API endpoints.
- Package, version, document, and deploy AI/ML models/services using MLOps frameworks like MLflow, Kubeflow, or an enterprise AI/ML tool such as Dataiku.
Inference Optimization
- Tune inference performance using model quantization, tensor parallelism, low-level optimization libraries (e.g., TensorRT, ONNX Runtime, DeepSpeed).
- Implement dynamic batching and request multiplexing for low-latency, high-throughput serving.
- Profile and monitor model inference workloads to identify and remove performance bottlenecks.
AI Infrastructure Management
- Design and manage scalable GPU/accelerator infrastructure (on-prem) for AI training and inference workloads.
- Maintain efficient GPU job scheduling with tools like Redhat OCP.
Security and Compliance
- Embed security throughout the AI deployment lifecycle including model validation, image signing, runtime protection, and API security.
- Ensure infrastructure complies with enterprise security standards (e.g., NIST, ISO 27001).
- Collaborate with security and compliance teams to perform threat modeling and secure deployment assessments.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, Statistics, or a related field
- 5+ years in DevOps, MLOps, with 2+ years focusing on AI/ML systems.
- Strong understanding of AI/MLOps practices and tools
- Hands‑on experience deploying and optimizing LLMs or transformer‑based models in production.
- Proficiency in container technologies (preferably Redhat OCP)
- Strong scripting and automation skills (Python, Bash, etc.).
- Familiarity with inference optimization techniques (quantization, batching, parallelism).
- Solid understanding of GPU infrastructure and performance tuning.
- Deep knowledge of secure software development practices and DevSecOps tooling
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.