Top AI Jobs in Singapore

Conduct research and design efficient, GPU-accelerated generative AI models (LLMs, vision, robotics), publish at top conferences, mentor interns, collaborate across teams, and transition research into products.

Embed with enterprise engineering teams to deploy and scale agentic LLM workflows (Devin), drive adoption through workshops and pair-programming, quantify productivity impact, create playbooks and enablement materials, and turn engagements into repeatable deployment models.

Own QA and evaluation systems for multilingual AI agents: build evaluation gates, AI-driven localization testing, annotation/eval infrastructure, and feedback loops to auto-publish translations safely at scale. Lead cross-functional delivery across engineering, AI, linguists, and design to turn subjective quality into measurable, automatable systems.

Design, build, and deliver end-to-end AI-enabled applications including retrieval pipelines, LLM orchestration, backend APIs and user interfaces. Own SDLC, CI/CD, containerisation, observability and secure cloud deployments. Integrate LLM APIs and vector DBs, evaluate models, contribute shared platform components, and work with business teams and AI PMs.

Lead product strategy and delivery for AI-enabled workflow products across design, tendering, construction management, and document intelligence. Define vision, roadmaps, requirements, KPIs, and partner with engineers, data teams, designers, and stakeholders to launch and iterate production AI features with governance, explainability, and human-in-the-loop tradeoffs.

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.

Lead technical architecture and delivery for AI automation, data integration, workflow automation, and platform capabilities. Design scalable, secure solutions, manage AI engineering delivery, set engineering standards, oversee data and inference-layer work, integrate SaaS/platforms, and establish governance, testing, and documentation for sustainable automation.

Embed with enterprise clients to design, build, and operationalize agentic AI solutions in production: architect integrations with ERP and identity systems, write production-grade code, build retrieval pipelines, agent orchestration, guardrails, evaluation suites and observability, manage cutover and handover to support, and produce reusable patterns and accelerators.

The Director of AI is responsible for solving complex AI challenges, exceeding client expectations, leading AI teams, and fostering ethical AI practices. They will create thought leadership and manage AI solutions from conception to commercialization while building client relationships and partnerships.

Design and build a production multi-agent harness and MCP integrations that operate across ERPs, CRMs, and business tools. Own end-to-end production concerns (reliability, observability, permissions, safe workflow execution), scope the product, make architecture decisions, and ship features working closely with CTO, product, engineering, and design. Stay current with agent frameworks and use tools like Claude Code in development.

As a Principal Machine Learning Engineer, you will lead a team, develop scalable machine learning solutions, and enhance ad serving efficiency for Grab's ads business.

Lead the development of AI tools that optimize the software development lifecycle, mentor teams, and implement scalable ML systems.

The Principal Software Engineer will develop AI tools to enhance developer productivity and manage AI project execution across teams.

Collaborate with teams to develop AI tools for enhancing software development efficiency, mentor engineers, and manage AI projects across Grab.

Lead the development of AI-driven software solutions, enhance engineering productivity, manage AI project execution, and mentor junior engineers.

The Senior Data Scientist will lead the development of chatbot technologies using machine learning and NLP to enhance user experience at Grab.

Generate and qualify new business opportunities for AI and PropTech solutions, conduct outreach, build pipeline, coordinate with sales and marketing, and communicate product value to prospective clients.