Top AI Jobs in Singapore

The AI Prompt and Quality Engineer is responsible for monitoring AI Chatbot responses, resolving quality issues, tuning models, analyzing data, and improving processes.

Design, develop, and deploy AI-powered solutions, integrating AI/ML models into applications while collaborating with data scientists and DevOps teams.

Lead the development and implementation of AI tools for enhancing engineering workflows, mentoring team members, and optimizing production-ready ML systems.

Lead AI-driven solutions scaling, product lifecycle ownership, enhancing automation, rapid prototyping, and cross-functional collaboration for business growth.

Join NTT DATA as an Associate AI/ML Engineer to develop and integrate machine learning solutions into software applications for various industries. Collaborate with teams, monitor model performance, and stay updated on AI/ML tools.

The AI Applied Engineer will develop and maintain integrations with AI ecosystems, collaborate with customers, and contribute to open-source projects while driving real business value through GenAI applications.

The Applied AI Engineer will onboard customers, guide integration of AI solutions, and collaborate on complex projects to ensure successful deployment and customer satisfaction.

The AI Solution Architect will conduct pre-sales activities, guide product implementation, and ensure customer satisfaction through ongoing support and optimization.

As an AI Solutions Architect, you will drive the adoption of Mistral AI solutions in the public sector, collaborating with sales and technical teams to ensure successful implementation and customer success.

As an Applied AI Engineer at Mistral, you will onboard customers, implement AI solutions, and collaborate on complex projects, utilizing DevOps expertise.

Lead AI engineering projects, develop scalable AI solutions, manage data science teams, and collaborate on analytics architecture while ensuring technical standards and best practices.

The AI Architect is responsible for designing complex solutions, managing projects from presales to delivery, and mentoring junior architects while ensuring alignment with business needs.

As a Senior Software Engineer, you will implement AI-driven solutions to enhance developer efficiency, manage AI projects, and mentor junior engineers at Grab.

The Senior Platform Engineer will architect, build, and maintain scalable AI and Data platforms, managing data pipelines and optimizing cloud solutions.

The Principal Cloud Engineer will architect, build, and maintain intelligent multi-cloud infrastructures, focusing on AI and data workloads, collaborating across teams to optimize workflows and drive innovation.

As a software engineer, you will develop and manage components of data management software, focusing on AI infrastructure at scale. Responsibilities include overseeing product lifecycle and learning new technologies.

Join WorldQuant's AI team to build and implement AI models for investment strategies, optimizing financial operations across the firm.

The role involves developing dynamic user interfaces for AI products, optimizing applications, creating reusable components, and collaborating with the AI team.

As a software engineer, you'll develop end-to-end data analytics and ML solutions, working with open-source tools and collaborating remotely with global teams.

The AI Infrastructure Platform Engineer will design and deploy AI networking solutions and optimize AI infrastructures in hybrid cloud environments, collaborating on automation and integration projects.

The AI Specialist will develop data pipelines, build predictive models, implement generative AI solutions, and collaborate with teams on AI projects.

Lead a team to develop and implement AI-driven productivity solutions, collaborating with stakeholders and promoting AI adoption throughout the organization.

As an AI Software Engineer, you'll design and deploy AI solutions, optimize models, collaborate with teams, and enhance APIs for performance.

Lead the exploration and assessment of AI technologies and models, ensuring relevance to the organization and collaborating with teams for effective implementation.

The Labelling Systems Engineer will design, verify, and manage labelling systems for medical devices, ensuring compliance with regulatory standards and user needs. Requires collaboration with cross-functional teams and contribution to continuous improvement of labelling processes.