Top AI Jobs in Singapore

Perform independent research analyzing high-dimensional neural data; develop and apply machine learning, computer vision, and dynamical-systems models; maintain lab software, contribute to grants, presentations, and manuscripts, and present at lab meetings.

Early-career full-time program offering training, mentorship, and hands-on work within Binance's blockchain ecosystem. Participants develop practical skills in Web3, collaborate across teams, and contribute to product and engineering projects while receiving tailored curriculum and 1:1 mentorship.

Lead design and execution of data and AI governance for a regional digital bank: define policies, lifecycle frameworks for ML/GenAI, implement governance tools and dashboards, coordinate incident response, and partner with data, MLOps, product, tech and risk teams to embed privacy, fairness and regulatory compliance across AI and data systems.

Operate and harden Kubernetes-based AI/MaaS production environments; define SLOs, alerting, dashboards, and runbooks; improve rollout safety with canaries and fast rollbacks; drive GPU capacity planning; automate operations with Helm, Argo CD, operators and scripts; and partner to debug incidents from API edge to model workers.

Lead end-to-end delivery of multi-region AI cloud infrastructure and platform software projects, coordinating cross-functional teams, vendors, and leadership to meet timelines, budgets, and quality standards for large-scale GPU deployments and cloud platform releases.

The Senior Executive will manage participant communications, screening, data monitoring, report submissions, and adherence to study protocols in clinical research.

In this role, you will lead the development of generative AI solutions, ensure AI safety and trust, and facilitate workshops while collaborating with researchers and industry to advance AI adoption.

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

Design, build, deploy, and operate secure backend services that enable AI/ML and generative-AI solutions for government systems. Implement model pipelines, prompt workflows, RAG solutions, APIs, integrations, evaluation and monitoring; support responsible AI controls, security compliance, deployment in approved cloud environments, troubleshooting, and operational support across development and production stages.

Design and build internal AI productivity tools and LLM-powered applications to augment developer workflows. Integrate AI into the software development lifecycle, apply techniques like prompt engineering, RAG, and agents, partner with engineering teams to identify bottlenecks, and continuously evaluate emerging AI technologies to improve internal platforms and engineering efficiency.

Lead technical design and delivery of core products across backend, frontend, APIs, databases and infrastructure. Hands-on coding, system design, code reviews, production debugging, mentorship, and driving engineering initiatives. Ensure reliability, observability, security, and scalable architectures while collaborating with product, design and AI teams to ship high-quality features.

Lead and manage a cross-functional engineering team to design, build, and operate scalable, reliable production systems for a payments app. Own delivery, architecture, code quality, observability, incident response, and engineer development while working closely with product, design, mobile, backend and AI teams to deliver customer-focused outcomes.

Lead data acquisition and partnership activities for Transport AI, developing a prioritized multimodal data roadmap, negotiating data access with agencies and industry, enforcing data standards and governance, building secure ingestion platforms, and working with legal, cyber and AI teams to onboard datasets for analytics and AI use cases.

Intern will research emerging AI technologies (LLMs, generative AI, RPA/OCR, NLP, computer vision), partner with business and tech teams to design and build prototypes/MVPs, document technical approaches for scaling, and integrate AI solutions into Marsh Risk systems. Role is hybrid in Singapore for 3–6 months (part-time acceptable).

Lead technical design and execution of major products and systems, write and review code, make architecture decisions, mentor engineers, drive initiatives from design to production, own reliability, testing, security and observability, and collaborate with product, design and AI teams to deliver scalable, maintainable systems.

Technical lead responsible for designing and shipping scalable backend and frontend systems, making architecture decisions, writing and reviewing code, mentoring engineers, improving reliability, tooling and observability, and owning production incidents from diagnosis to resolution while collaborating with product, design and AI teams.

Lead technical design and execution of a scalable AI-native email product. Hands-on coding, system design across backend/frontend/APIs/databases/cloud, code review, production debugging, mentoring engineers, improving tooling, and owning reliability from design through incidents.

Lead and grow a cross-functional engineering team to design, build, and operate scalable, reliable production systems. Drive architecture, code quality, observability, incident response, and engineering processes while collaborating with product, design, mobile and AI teams to deliver customer-focused outcomes.

Lead and manage a cross-functional engineering team to design, build, and scale customer-facing products. Own engineering delivery, architecture, code quality, observability, reliability and incident response. Collaborate with product, design, mobile, backend and AI teams. Coach engineers, manage performance, improve processes and tooling, and drive fast, outcome-focused delivery.

Lead AI operational excellence across the SEAO region by analyzing processes, standardizing SOPs, coordinating AI projects end-to-end, managing governance and platform administration, and delivering dashboards and executive reporting to drive adoption and measurable business value.

6-month internship to develop and integrate agentic AI systems and RAG pipelines, connect agents to internal data/APIs, build prototypes, and measure agent impact alongside data analysts and engineers.

Participate in a 14-day notification-sorting pilot using a Google Pixel 9+ as primary phone. Interact naturally with apps that generate notifications, complete daily sorting tasks and short feedback forms, and report technical issues. Must follow confidentiality and Upwork platform requirements.

Design, build, deploy and maintain scalable AI/ML applications, LLM services and data pipelines. Collaborate with data scientists and product engineers, ensure performant, reliable, and well-tested code, influence roadmap, and provide technical leadership and mentoring.

Design, build, and deploy AI-enabled products (RAG, retrieval, reasoning) and supporting web systems and data pipelines. Integrate emerging AI technologies, prototype rapidly, collaborate with cross-functional teams, and ensure robust, scalable, and secure software solutions that meet analyst needs.

Design, build and deploy scalable full-stack web features, focusing on an internal AI-powered chat assistant. Ensure high-quality, well-tested code, maintain production reliability, participate in code reviews, collaborate with designers and stakeholders, and contribute to documentation and Agile delivery.