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Ability to cope with reasonably high level of stress and demonstrate resiliency, drive and professional integrity.
Has strong in-depth knowledge in both DC facility management & DC Operations functions
Strong technical and functional knowledge of Data Centre critical systems, including diesel generators, UPS systems, fuel systems, switchgear, power distribution equipment, chillers, computer room air handlers, fire detection/suppression and building monitoring system
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Oversee the design, testing and global deployment of AI-driven editorial tools and workflows, ensuring seamless integration with existing technologies and platforms
Develop and maintain global standards and guidelines for AI-generated or AI-optimised legislative content, ensuring accuracy, compliance, and copyright alignment
Champion AI-first editorial practices, helping teams adopt new tooling, improve editorial decision-making and reduce manual work through automation
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Develop Secure Deployment Guardrails: Build tenant-owned Model Context Protocol (MCP) servers and highly restricted API wrappers that allow AI agents to safely interact with Grab’s core Risk Engine without risking platform stability.
Optimize System Reliability: Own the technical stability, latency optimization (e.g., resolving deep asyncio blocking bugs), and token-cost efficiency of our internal agent platforms so our Data Analysts can focus purely on the Risk domain
Collaborate as a Systems Fusion Expert: Partner closely with domain-expert Data Analysts to translate their tacit Trust & Safety knowledge into structured, machine-readable formats and scalable agentic skills.
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Incorporate and implement adjustments to the Air Manpower Organisation structures during implementation, and lead post-implementation reviewsChallenge(s)
Navigating organisational change and building consensus among diverse stakeholders
At least 6 years of relevant experience in HR, change management, organisational design or manpower planning
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Reusable AI capabilities, enterprise knowledge assets and common product standards that accelerate delivery across multiple business domains.
Strategic AI-enabled products that improve educator productivity, organizational capability and outcomes for children and families.
Strong partnerships across business units, Technology teams, government agencies, Institutes of Higher Learning and the broader innovation ecosystem.
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Build responsive, accessible, and performant web interfaces, using AI to speed up development while retaining full ownership of architecture and reusability.
Design and operate secure, reliable, and observable backend services and APIs, guiding AI for boilerplate and tests while owning API contracts and data models.
Review and validate all AI-generated code, identifying hallucinations, logic flaws, and maintainability issues before integration.
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Research and evaluate other state-of-the-art AI techniques relevant to robotics, including object detection, semantic segmentation, depth estimation, and scene understanding.
Perform accurate calibration of on-robot sensors including cameras and LIDAR.
Design, implement and maintain firmware logic, architecture and device-to-device communication using standard protocol (CAN, I2C, SPI) with a focus on reliability, latency and power constraints.
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Collaborate with stakeholders to gather requirements, recommend technology solutions, and deliver digital transformation initiatives from concept to implementation.
Develop reusable frameworks, standards, documentation, and training materials to support sustainable process excellence.
Provide user support, troubleshoot deployed solutions, and ensure the successful delivery and continuous improvement of projects.
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Implement automation to improve repeatability and reduce manual tasks in the development pipeline, such as auto-code generation, static code analysis, and intelligent error detection.
Integrate automation tools that improve developer productivity, streamline testing, and optimize release cycles.
Stay current with the latest advancements in Al and machine learning technologies.
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Partner closely with IC design teams to ensure to deliver comprehensive technical specifications, rigorous benchmark reports, and high-value patent proposals.
Education: Ph.D. in Computer Science, Electronic Engineering, Automation, or a highly related technical field.
Technical Expertise: Deep foundational knowledge in computer architecture, specifically regarding GPU/NPU microarchitecture implementation.
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