Top AI Jobs in Singapore

Design, deploy, and scale production AI systems and applications. Responsibilities include building data pipelines, tuning and hardening models, collaborating with researchers, engineers, and product managers, monitoring live models, tracking AI advances, conducting code reviews, and owning solutions end to end amid changing priorities.

Research and develop novel AI models, algorithms, and systems; validate them through rigorous experiments and large-scale distributed training; and transition prototypes into production. The role involves deep learning, LLM pre-training and alignment, efficient GPU/TPU utilization, scientific analysis, technical writing, mentoring, code and paper reviews, open-source contributions, and end-to-end project ownership.

Lead and scale an AI-driven creative design team producing performance marketing assets for paid media. Own creative direction, production workflows, quality control, testing, and performance-driven iteration. Develop AI tool expertise, prompt and style libraries, and automated workflows with engineering partners. Collaborate with marketers, media buyers, copywriters, producers, and video editors while remaining hands-on with design and AI tools.

Leads Igloo’s enterprise technology solutions portfolio, positioning, productisation roadmap, complex enterprise sales cycles, solution design, and commercial pipeline. Translates platform capabilities into business value for insurers, banks, fintechs, and digital platforms; oversees architecture, integrations, security posture, ROI cases, and implementation handoffs. Builds ecosystem partnerships and develops a solutions and enterprise go-to-market team across Southeast Asia.

Develop machine learning, statistical, optimization, computer vision, Generative AI, and advanced analytics solutions for smart manufacturing. Analyze operational data, deploy production-ready AI models, monitor performance, and collaborate with manufacturing, engineering, supply chain, quality, IT, and software teams to improve quality, productivity, reliability, and decision-making across global operations.

Leads Microsoft 365 Copilot adoption across Singapore’s Ministry of Home Affairs agencies. Delivers basic and advanced Copilot, Agent Builder, and Copilot Studio training; develops AI agents; creates enablement materials; enables internal trainers; manages stakeholder engagement, change programs, adoption measurement, and governance within a secure government environment.

Intern will work with mentors to define, prototype, validate, and demonstrate AI solutions. Responsibilities include developing Generative AI and Agentic AI workflows, prompt engineering, RAG, data-driven prototyping, and enhancing AI frameworks using Python, Databricks, and AWS. The role also explores OCR, image recognition, and multimodal AI use cases while translating business needs into technical approaches.

Lead design and build of an end-to-end AI contract-review agent: prompt orchestration, RAG pipelines, fine-tuning, web UI and tooling, data/model infra, deployment (CI/CD/cloud), and product-driven features like assumption mapping and contract diagnostics.

Lead enterprise technical sales engagements focused on developer productivity, AI-assisted development, and Agentic SDLC adoption. Design secure, scalable architectures, conduct proofs of concept, hackathons, code-with sessions, and architecture workshops, and guide customers through DevOps, cloud-native development, and AI platform adoption. Partner with developers, engineering leaders, and Microsoft product teams to resolve technical blockers, shape solutions, and connect productivity, quality, security, and delivery improvements to business outcomes.

Design and deploy advanced process control, automation, and analytics solutions for semiconductor manufacturing. Collaborate with process teams to apply statistical analysis and machine learning, maintain global control applications, develop training, and integrate AI-assisted tools to improve yield, quality, and efficiency.

Lead data-driven process and test integration initiatives to improve high-value-bits yield (PG2+). Develop models and monitoring for tool performance, equipment prognostics, and test optimization. Prototype solutions with cross-functional teams, deploy best-known-methods to production, and integrate AI-assisted tools to drive continuous improvement and operational excellence.

Build and operate production-grade agentic AI solutions in a customer-embedded role. Develop full-stack systems and AI agents, manage Azure infrastructure, maintain CI/CD pipelines and container platforms, handle monitoring and security alerts, administer IAM/RBAC, perform backups, manage costs, and support Day 2 operations. The role requires direct customer collaboration, technical delivery ownership, secure government-environment work, and eligibility for Singapore Government security clearance.

Six-month hands-on marketing internship focused on SEO-driven content, campaign and growth initiatives, content creation for multiple channels, basic design of marketing assets, influencer outreach, conference support, and competitive/market research to improve product and go-to-market performance.

Designs and deploys Microsoft 365 Copilot and custom AI agents using Microsoft Agent Builder and Copilot Studio. Delivers Copilot and agent-development training, supports enterprise adoption, advises clients, troubleshoots implementations, and creates enablement materials. The role requires integrating Microsoft 365 services and enterprise data while complying with strict security and government data-handling requirements. It is client-facing, on-site in Singapore, and includes work with secured government facilities.

Develop, train, evaluate, optimize, and deploy machine learning and deep learning algorithms for intelligent surveillance products. Responsibilities include data preprocessing, feature engineering, model research, algorithm integration, inference optimization, documentation, and collaboration. The role focuses on target detection, feature extraction, tracking, recognition, and applying emerging AI technologies to business problems.

Develop and optimize machine learning and deep learning algorithms for surveillance and monitoring applications. Train, evaluate, and improve models; perform data preprocessing, feature engineering, and labeling coordination. Research computer vision algorithms for detection, feature extraction, tracking, and recognition, then integrate models into products across deployment platforms. Document experiments, communicate findings, and collaborate on complex AI projects and innovations.

Owns full-cycle enterprise sales for Cloudera’s supported OEM Mistral offering and Anywhere Cloud, from prospecting and proof of concept through negotiation, close, renewal, and expansion. Manages complex, multi-threaded deals, executive relationships, pipeline, forecasting, and quota attainment. Coordinates account executives, partners, engineering, product, legal, implementation, and solution specialists while positioning AI within customers’ data strategies and hybrid technology environments.

Supports Finance transformation by identifying and evaluating AI, digital, automation, and analytics opportunities. Gathers business requirements, maps current and future processes, facilitates workshops, supports pilots, and documents recommendations. Develops user guides, prompts, training materials, and adoption initiatives for Microsoft 365 Copilot and other approved tools. Collaborates with Finance users, Technology, Data Office, and vendors to improve efficiency, controls, productivity, and data-driven decision-making.

Leads data and AI governance strategy across Group Marketing and Communications. Establishes data ownership, quality standards, metadata, lineage, risk controls, responsible AI practices, and regulatory readiness. Oversees marketing data governance initiatives, resolves systemic data issues, manages governance tooling, and partners with senior Marketing, Technology, Compliance, and Data stakeholders to drive enterprise-wide change and trusted data use.

Develop, train, evaluate, optimize, and deploy machine learning and deep learning algorithms for intelligent surveillance products. Responsibilities include data preprocessing, feature engineering, labeling coordination, model innovation, algorithm integration, research into emerging AI technologies, and documentation. The role covers audio and video algorithms such as detection, feature extraction, tracking, and recognition, with collaboration across technical teams.

Develop and execute technical SEO and Generative Engine Optimization strategies for Western markets. Conduct audits covering crawling, indexing, site architecture, Core Web Vitals, structured data, and performance. Manage SEO tools, monitor rankings and organic traffic, optimize content and technical assets, improve visibility across Google and AI-powered search platforms, and collaborate with developers, content teams, and marketing stakeholders.

Lead the incubation, architecture, and enterprise deployment of applied AI, generative AI, agentic workflows, predictive intelligence, and decision platforms across JAPAC. Advise senior executives on AI transformation, establish governance and observability standards, manage experimental initiative prioritization, mentor data science and ML teams, and promote AI literacy across commercial organizations.

Conduct independent research on frontier AI evaluation and auditing. Design rigorous evaluations, audit methods, and reproducible experimental pipelines; analyze model capabilities, risks, robustness, and alignment-relevant behavior. Produce audit reports, recommendations, publications, tools, and presentations while collaborating with technical, policy, engineering, and standards teams. The role requires careful handling of confidential information and may involve pilot audits with frontier AI companies.

Design, build, and deploy production AI applications, including retrieval pipelines, LLM orchestration, APIs, and user interfaces. Own the software lifecycle, integrate model and vector database technologies, evaluate performance, manage CI/CD and cloud operations, and contribute reusable platform components. Collaborate with business teams and AI product managers while documenting architecture, communicating risks, and improving applications after launch.

Leads end-to-end digital transformation engagements, framing ambiguous problems, designing AI-enabled solutions, managing delivery, driving organizational adoption, and advising senior stakeholders. Oversees cross-functional teams, workshops, prototyping, agile delivery, change strategies, responsible AI practices, and capability building. Coaches junior consultants and develops reusable delivery playbooks. Requires strong consulting, transformation, operating model, stakeholder management, AI fluency, and structured problem-solving experience.