Top AI Engineer Jobs in Singapore

This internship involves assisting in machine learning development, AI automation, data engineering, and exploring innovative projects to enhance test efficiency and engineering productivity.

The role involves developing AI and ML solutions for semiconductor workflows, training Citizen Data Scientists, and integrating intelligent agents into engineering processes.

The Principal AI Engineer leads the design and operationalization of complex AI systems, architecting multi-agent solutions while ensuring safety, reliability, and performance. They mentor engineers and improve processes and products based on measurable outcomes.

Lead technical decision-making and development for core infrastructure, optimize distributed systems, and mentor engineers while working with AI-driven products.

The Senior AI Engineer designs and develops scalable AI/ML systems, operationalizes models, ensures reliability and observability, and mentors junior engineers.

As a Senior AI Engineer, you will develop AI solutions to enhance customer support and internal efficiency, design APIs, and collaborate with teams in a fast-paced environment.

The Staff AI Engineer will lead the development of AI solutions, set technical vision, design robust APIs, and enhance user experience through innovative language technologies.

Lead the design, development, and integration of AI-powered applications while ensuring code quality and collaborating across teams. Ideal for engineers focused on automation and secure application engineering.

Design, build, and productionize GenAI and ML solutions for semiconductor engineering: large-scale data pipelines, LLM/RAG and agentic workflows, model training/inference, analytics, deployment, monitoring, and cross-functional collaboration to improve quality, cost, and engineering productivity.

As a Machine Learning Engineer Intern, you will build data pipelines, develop models, and collaborate on data-driven solutions in manufacturing. Gain experience with cloud platforms and MLOps.

As a Solutions Architect at CoreWeave, you'll lead the technical relationship with customers to optimize AI workloads on cloud infrastructure, focusing on Kubernetes and HPC environments.

Develop and deploy AI and ML solutions, design microservices architectures, mentor teams, and lead technical discussions to innovate AI applications.

The Sr. Staff AI Engineer will design and build a high-performance software platform for AI workflows, focusing on systems architecture, AI agent development, and CI/CD excellence. Responsibilities include defining technical roadmaps, prototyping AI technologies, and ensuring system quality across teams.

Design, develop, and deploy agentic AI solutions to optimize network automation, predictive maintenance, anomaly detection, and intelligent network management. Collaborate with networking stakeholders to translate goals into technical requirements, ensure compliance with performance, risk, and regulatory standards, research emerging agentic AI trends, and provide troubleshooting, QA, and documentation for production AI systems.

The Staff AI Forward Deployed Engineer will develop and produce GenAI solutions, serve as a trusted advisor to clients, and collaborate with cross-functional teams to influence product direction.

Early-career AI engineer who ships production features rapidly using AI-augmented workflows. Own end-to-end features, prototype and evaluate LLM-driven solutions, collaborate with PMs and customer teams, pair with senior engineers, and maintain clear, tested, maintainable code while measuring impact.

Architect and implement scalable generative-AI solutions for enterprise document workflows. Own end-to-end delivery from customer discovery through deployment, build advanced extraction and automation systems, ensure privacy/security by design, mentor engineers, and collaborate with product and commercial teams to drive customer adoption and measurable business value.

Design and build company-wide AI knowledge infrastructure and context layers, develop scalable LLM application architecture (RAG, vector DBs, prompt workflows), own end-to-end delivery of internal AI tools, optimize performance and inference, evaluate/integrate AI tooling, and mentor junior engineers while translating business needs into technical roadmaps.

Lead design, build, and deploy agentic AI and RAG solutions for networking. Architect scalable AI workflows, mentor engineers, establish MLOps/DevOps pipelines, optimize model performance, and collaborate with networking teams to deliver production AI systems and governance.

Develop and deploy enterprise-grade AI and Generative AI solutions, working on applications like LLM and RAG, ensuring operational stability.

Develop AI solutions utilizing large language models to boost productivity, lead end-to-end development of AI systems, and integrate AI into business workflows and processes.

Lead and deliver agentic AI solutions for networking: design RAG and agent architectures, oversee development and deployment, mentor engineers, establish MLOps/DevOps pipelines, optimize performance and governance, and collaborate with networking stakeholders to drive AI strategy and operationalize network automation and anomaly detection.

Build, test and sustain AI agents, RAG/vector search and platform integrations for ETP Hub. Develop retrieval, embedding, indexing and user-facing AI tools, create API connectors and automation scripts, document workflows, and support deployment, monitoring and refinements to improve search, retrieval and operational efficiency.

The role involves designing and deploying generative AI solutions, mentoring junior engineers, collaborating with teams, and optimizing system performance.

Serve as a Solution Architect to drive revenue and customer adoption of the Cloudflare AI/Developer Platform, advising on technical sales and solutions. Collaborate with teams, present to customers, and lead strategic initiatives.