Assist with storage and data-path investigations (mounts, connectivity, client-side symptoms) on high-performance platforms, gathering evidence for Senior or Engineering-led diagnosis
Follow established runbooks to resolve common issues; propose improvements and contribute incremental fixes with review
Accurately record, update, manage, and resolve tickets, keeping all parties informed with clear notes, next steps, and customer communications via the agreed channels
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Strong problem-solving, critical thinking, and process-optimization mindset, with the ability to map workflows and identify opportunities for automation.
Clear written and verbal communication skills, with the ability to document guidelines, create simple playbooks, and collaborate with cross-functional teams.
Comfort working in a hybrid environment in WP Kuala Lumpur, with good time management and self-directed learning skills.
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Mentorship: Assist in supervising 1–2 PhD students or junior researchers and support their research development.
A Master’s or PhD degree in Chemistry, Chemical Engineering, Materials Science, Physics, Computer Science, or a related discipline.
Demonstrated research experience in computational chemistry, atomistic simulations, machine learning, or artificial intelligence for materials and catalysis.
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Use AI responsibly to accelerate engineering productivity while retaining accountability for code quality, design correctness, testing, security, and production readiness.
Partner with product owners, architects, security, operations, and business stakeholders to translate business outcomes into executable engineering plans.
Review solution designs, code, tests, and operational readiness to ensure consistency with enterprise architecture, security, compliance, and engineering standards.
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• Support periodic review activities for laboratory equipment/system/methods, including REE, user access and audit trail review Deliver Administrator responsibilities for laboratory equipment/ systems/ methods
• Coordination of Change Request related to LIMS and other routine tasks as needed.
• Perform LIMs periodic system audit trail reviews Other assigned AS&T and LIMS tasks as applicable
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Research & Analysis: Conduct research and analysis to support the development and refinement of the AI system.
Stakeholder Coordination: Coordinate with cross-functional teams and internal stakeholders to facilitate smooth planning and execution.
Integration Project Execution: Support the project management and execution of integration plans and key workstreams for specific entities to be within timelines.
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You should hold a Degree or Diploma in Telecommunications, Network Engineering, Electrical/Electronics Engineering, Construction Management or a related discipline, with approximately 4-10 years of experience delivering network infrastructure construction or deployment projects. Candidates from structured cabling, telecommunications, network infrastructure, data centre fit-out or systems integration environments will be well suited. Practical experience with copper and fibre cabling, fibre testing, rack and cabinet installation, cable containment, network equipment deployment, testing and commissioning support, and subcontractor management is required. Familiarity with data centre network environments, including leaf-spine architecture, switches, routers, firewalls, OOB networks and MMR/MDF/IDF deployments, will be useful. Experience with greenfield or brownfield data centre projects and relevant cabling, fibre optic or networking certifications would be advantageous.
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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Master's or Ph.D. candidates in Computer Science, Computer Engineering, Artificial Intelligence, Mathematics, Computational Physics, Computational Chemistry, or other related quantitative disciplines.
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The AI Engineer (Full Stack Engineering) is responsible for the design, development, and maintenance of cloud native/modern software solutions, increasingly built in partnership with AI coding agents and copilots. Success in this role depends as much on strong upfront architecture, design, and specification skills as it does on hands-on coding – and on the ability to clearly articulate intent, constraints, and acceptance criteria so that both AI systems and human collaborators can execute against them reliably.