AI Jobs in Singapore

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Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help customers achieve success. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

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Collaborate closely with researchers, AI engineers, and product engineers on complex customer projects, integrating cutting-edge AI models into clients' software products. Design, develop, and maintain scalable and robust full-stack applications, ensuring seamless integration between front-end and back-end systems. Develop complex use cases with customers, providing guidance and ensuring the best production integration with back-end and front-end interfaces. Collaborate with product and science teams to continuously improve product and model capabilities based on customer feedback.

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Work with enterprise customers and internal teams to turn business workflows into scalable, production-ready agentic AI systems. Design and build LLM-powered agents that reason, plan, and act across tools and data sources with enterprise-grade reliability. Balance rapid iteration with enterprise requirements, evolving prototypes into stable, reusable solutions. Define and apply evaluation and quality standards to measure success, failures, and regressions. Debug real-world agent behavior and systematically improve prompts, workflows, tools, and guardrails. Contribute to shared frameworks and patterns that enable consistent delivery across customers.

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Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help customers achieve success. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.

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As a Member of Technical Staff, Applied ML, you will work directly with enterprise customers to design and deliver custom LLM solutions that address high-value problems by rapidly understanding customer domains. You will train and customize frontier models using Cohere's foundation model stack, CPT recipes, post-training pipelines including RLVR, and data assets. Additionally, you will develop state-of-the-art modeling techniques to enhance model performance for customer use cases and contribute improvements back to the foundation-model stack, including new capabilities, tuning strategies, and evaluation frameworks. You are expected to translate ambiguous business problems into well-framed ML problems with clear success criteria and evaluation methodologies. Part of your role also includes functioning within a customer-facing MLE team to identify opportunities where LLMs can create transformative impacts for enterprise customers, while operating with early-startup ownership to set a high technical bar and define the role of Applied ML at Cohere.

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Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.

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Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) empowered to make implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from Data Scientists and Simulation Engineers using the product.

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Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.

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The role involves building a platform used by Data Scientists and Simulation Engineers to build, train, and deploy Deep Physics Models. The candidate will work on a focused, stream-aligned, and cross-functional team that includes back-end, front-end, and design members, empowered to make its own implementation decisions towards meeting its objectives. Responsibilities include gathering and leveraging domain knowledge and experience from the Data Scientists and Simulation Engineers using the product, taking ownership of work from implementation to production, ensuring quality, scalability, and observability at every step, which includes testing, containerization, continuous integration and delivery, authentication, authorization, telemetry, observability, and monitoring.

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Take part in building a platform used by Data Scientists and Simulation Engineers to build, train and deploy Deep Physics Models. Work on a focused, stream-aligned and cross-functional team (back-end, front-end, design) that is empowered to make its implementation decisions towards meeting its objectives. Gather and leverage domain knowledge and experience from the Data Scientists and Simulation Engineers using your product.