Top AI Jobs in Singapore

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, build, operate and maintain hybrid enterprise AI platforms with automation-first practices. Ensure reliability, scalability, observability, and performance; collaborate with architects, AI engineers, infra and network SMEs; troubleshoot and resolve production issues.

Assist in developing and supporting automation and AI solutions, including business analysis, programming, testing, and documentation activities while collaborating with diverse 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.

Lead identification, framing and orchestration of high-value data and AI initiatives across the region. Define strategic KPIs, build business cases, prioritize use cases, and translate approved initiatives into delivery and adoption plans. Drive product adoption, change management, upskilling and measurement of business impact; liaise with Finance, HR/P&O, President Office, tech and data teams to ensure alignment, readiness and sustained value realization.

The AI Scientist will develop frameworks to evaluate and audit Reinforcement Learning systems, ensuring safety and performance while leveraging advanced ML techniques.

The role involves solving complex customer issues, providing technical guidance, using automation for internal tools, and collaborating with other teams to enhance customer experience.

The Responsible AI Specialist will develop AI governance standards, conduct risk assessments, engage stakeholders, and promote ethical AI practices across UOB.

Design, develop and roll out geospatial AI-centric MVPs and digital products. Work full-stack on frontend and backend, implement and fine-tune ML/GenAI/LLM models, use cloud and DevSecOps practices, collaborate with stakeholders in cross-functional teams.

Lead innovative research in AI/ML technologies, mentor researchers, collaborate across teams, and advocate for ethical AI at Temus, driving national-scale initiatives.

The intern will support AI & Data projects by analyzing data, developing machine learning models, and assisting with data visualization and preprocessing.

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.

Build and deploy AI applications, collaborate with clients, solve technical issues, provide guidance, and ensure ethical standards in AI development.

The role involves designing, building, and deploying AI applications, particularly large language models, while leading teams and advising clients on AI solutions.

The Product Manager for AI Trading will define and ship AI features, manage the product lifecycle, and collaborate cross-functionally, focusing on user experience in crypto trading products.

Lead and manage a high-caliber AI team while overseeing the delivery of autonomous AI Agent products and ensuring alignment with business goals.

The Senior Advisory Specialist leads client engagements, coordinates tasks, ensures service delivery, mentors junior staff, and drives best practices in governance, risk, and compliance (GRC).

The AI Product Manager defines product strategies, collaborates with engineering and data teams, and oversees AI product development and performance evaluation.

Develop and optimize AI algorithms for computer vision tasks, including deep learning and few-shot learning approaches, while ensuring high-performance implementations and production readiness.

The AI and ML Solution Architect designs and implements AI/ML solutions, collaborates with teams, and improves product performance through advanced algorithms.

The Business Development Manager at HPE drives growth through strategic partnerships with NVIDIA, focusing on expanding market presence and supporting sales enablement for AI solutions.