AI Jobs in Singapore

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Contributors design original computational statistics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve using libraries such as Numpy, SciPy, and Sympy, ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems that require non-trivial reasoning chains in areas including number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly with verified correct answers.

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Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.

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As a Robotics Application Engineer specializing in Intelligent Manufacturing Automation, the responsibilities include closely collaborating with the automation group and industry partners to advance manufacturing automation by extending capabilities and solutions. Daily tasks involve integrating and developing robotics solutions, including processes, software features, and integrating state-of-the-art AI for manufacturing automation. The role includes working with the team leading the deployment of impactful robotic systems in production. Additional responsibilities entail contributing to the technical development and integration of advanced robotic automation solutions for manufacturing automation using the Intrinsic platform, ROS, and AI capabilities, collaborating with research and industry partners to integrate AI and automation into factory settings, and documenting designs, processes, and results while communicating effectively with internal technical teams and partners.

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The role involves defining the internal AI roadmap by partnering with Security, Legal, and business leaders, operating the enterprise AI stack including LLMs, vector databases, and gateways, enforcing consistent patterns for tool calling, prompt versioning, state management, and error handling to prevent fragmented agent implementations, and managing the full model lifecycle from evaluation and testing to upgrades and deprecations. The position includes proactively interviewing teams like Talent, Support, and Sales to identify manual workflows for automation with agentic AI, independently building and deploying proof of concepts to demonstrate ROI before scaling, owning the token procurement process, building forecasting and chargeback models to control spend, creating dashboards to track SLAs and system performance, and identifying opportunities for cost-saving and performance tuning.

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Forward Deployed Engineers lead complex end-to-end deployments of frontier models in production alongside strategic customers, owning discovery, technical scoping, system design, build, and production rollout. They operate across multiple deployments from prototype to stable production, build full-stack systems to deliver customer value, embed closely with customer teams to understand needs, guide adoption, scope work, sequence delivery, remove blockers, make trade-offs between scope, speed, and quality, contribute directly in code when necessary, codify working patterns into reusable tools and playbooks, share field feedback to help Research and Product teams improve models, and keep teams moving with clarity and follow-through.

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Contributors design original computational mathematics problems simulating real mathematical research workflows. They create problems that require Python programming using libraries such as Numpy, SciPy, and Sympy for solutions, ensuring these problems are computationally intensive and cannot be solved manually within reasonable timeframes. They develop problems involving non-trivial reasoning chains in areas such as number theory, combinatorics, graph theory, and numerical analysis. Problems should be based on real research challenges or practical mathematical applications. Contributors verify solutions using Python with standard mathematical libraries and document problem statements clearly while providing verified correct answers.

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Contributors may design original computational mathematics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve (using Numpy, SciPy, Sympy), ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks), develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly while providing verified correct answers.

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Design and deliver production-grade AI agents that are central to Sierra's growth, ensuring they are highly performant, reliable, and scalable in production environments across industries such as finance, healthcare, and commerce. Drive the Agent Development Life Cycle (ADLC) with complete ownership and autonomy from initial pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production and defining ADLC best practices. Partner directly with leaders at large enterprises and cutting-edge startups to understand their business challenges and build AI agents that transform operations at scale. Build the future of Sierra's platform by gathering customer feedback, prototyping new tools and features, and collaborating with research, product, and platform teams to enhance AI agent development and Sierra's product. Work on projects including designing AI agents to manage subscription churn, developing agents for complex customer interactions, creating industry-specific AI agent frameworks, facilitating design partnerships for new product initiatives, and experimenting with latest voice models for enterprise-grade integration.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, driving revenue directly to Sierra's growth. Take complete ownership of the Agent Development Life Cycle (ADLC) from initial pilot through deployment and continuous iteration, including building, tuning, and evolving AI agents in production environments while defining best practices. Partner directly with leaders of large enterprises and cutting-edge startups to understand business challenges and build AI agents that transform operations at scale. Work with customers to guide the evolution of Sierra's core platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape the future of AI agent development and Sierra's product.

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Design and deliver production-grade AI agents that are highly performant, reliable, and intuitive, running in production environments across industries like finance, healthcare, and commerce. Drive the Agent Development Life Cycle (ADLC) with complete ownership and autonomy from pilot through deployment and continuous iteration, building, tuning, and evolving AI agents in production and defining ADLC best practices. Partner with large enterprises and startups to understand business challenges and build AI agents that transform operations at scale. Build the future of Sierra's platform by surfacing unmet needs, prototyping new tools and features, and collaborating with research, product, and platform teams to shape AI agent development and product evolution.