Top AI Engineer Jobs in Singapore

Lead end-to-end design and implementation of generative AI solutions and APIs to improve customer-facing and internal automation. Build scalable, high-concurrency backend systems, collaborate with cross-functional teams, set best practices, and mentor engineers while driving deployment and MLOps for production AI products.

Lead design and delivery of generative AI agents and architectures, build robust APIs and scalable systems, roadmap AI applications, collaborate cross-functionally, troubleshoot production issues, and drive internal efficiency and customer-facing AI solutions.

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.

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

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 design and build of high-performance distributed data infrastructure and AI enablement platforms. Optimize systems internals and JVM performance, implement lakehouse and real-time streaming, develop scalable vector indexing and AI knowledge platform, own SDLC for petabyte-scale systems across global regions, drive engineering best practices, and mentor mid-level engineers.

Lead a Singapore-based team to design, build, and maintain scalable data infrastructure and self-service developer tooling. Implement robust, maintainable systems, ensure quality through testing and troubleshooting, collaborate cross-functionally, and mentor engineers while staying current with emerging technologies.

Lead design, build, and operate distributed, large-scale (batch/streaming) data platforms and pipelines. Drive technical decisions, performance optimization, data architecture (lakehouse), tooling standards, third-party integration, and mentor junior engineers to enable company-wide data-driven capabilities.

As a Senior Data Platform Engineer, you will design and optimize data infrastructure, develop data processing systems, and mentor junior engineers to drive data-driven initiatives.

Lead the Data DevOps team by developing and maintaining data infrastructure, enhancing tooling for self-service capabilities, and ensuring software quality and functionality.

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

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.

Prototype and implement AI-enabled workflows and product features; experiment with prompts, model behavior, evaluation methods, and integrations; collaborate cross-functionally to scope and ship solutions; apply structured testing and documentation to improve AI output reliability; research emerging tools, methods, and APIs.

Lead AI engineering practice, guiding design and delivery of Generative AI solutions while mentoring a cross-functional team. Collaborate with stakeholders, establish best practices in AI engineering, and ensure high standards in system performance and reliability.

The AI Engineer (Safety) will lead development of safety models, ensuring AI models are safe for Southeast Asian contexts by designing safety strategies and identifying culturally grounded risks.

The AI Engineer will lead AI projects, train apprentices, develop AI technologies, manage recruitment, and support industry activities.

As a Fullstack AI Engineer, you will design and maintain AI-powered applications, develop Proof-of-Concepts, enhance AI frameworks, and collaborate on production-grade systems in a cloud-native environment.

As an AI Engineer, you'll build prototypes, design system architectures, write code, integrate AI services, and manage deployments, ensuring software solutions meet public sector needs.

The AI Engineer builds prototypes, designs system architectures, writes production-quality code, manages deployments, and collaborates on AI platform services for government applications.

Design, fine-tune, and deploy generative AI/LLM solutions (LoRA/PEFT). Build RAG pipelines, embeddings, vector DBs, knowledge bases, and evaluate hallucination. Advise on guardrails and collaborate across teams.

Design and deliver production-ready AI and data science solutions across CRM, retail, marketing and operations. Build ML models, GenAI/RAG pipelines, feature engineering and training workflows; collaborate with data engineering to deploy, monitor and optimize models; run experiments and measure business impact while ensuring responsible AI, security and governance.

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.