Total 291 F&B / Tourism / Hospitality job vacancies

Principal Engineer / Manager, Defect Detection & Yield Engineering

Key Responsibilities

• Lead defect detection and yield improvement initiatives across semiconductor manufacturing operations.

• Drive root cause analysis and corrective actions for process and quality excursions.

• Analyze defect and yield data to identify trends and improvement opportunities.

• Partner with Process, Manufacturing, Quality, and Engineering teams to improve operational performance.

• Support implementation of advanced inspection and monitoring solutions.

• Develop best practices and mentor engineers within the organization.

Requirements

• Degree in Engineering, Materials Science, Physics, or related discipline.

• 7+ years of semiconductor manufacturing, yield, process, or defect engineering experience.

• Strong analytical, problem-solving, and stakeholder management skills.

• Experience in defect analysis, process monitoring, and yield improvement.

• Ability to lead cross-functional initiatives in a fast-paced environment.

As a NAND Reliability Product  Engineer, you will be responsible for defining, evaluating, and safeguarding the Extrinsic/Intrinsic reliability of Micron’s NAND Flash products. You will work hands‑on with large‑scale data analysis, electrical failure analysis, and cross‑functional teams to ensure robust product reliability and prevent escapes to customers.

This role offers deep technical ownership at the intersection of device physics, circuits, process technology, and product engineering, with strong visibility across development and manufacturing organizations.

Key Responsibilities

• Define and implement NAND Flash reliability test flows to assess product reliability performance and prevent extrinsic/intrinsic reliability escapes.

• Perform high‑volume statistical data analysis to evaluate NAND DPM/ intrinsic reliability risks and trends.

• Drive electrical failure analysis, including  advance characterization, to identify root causes and solution spaces.

• Develop short‑term countermeasures such as targeted stresses and screens, applying knowledge of digital/analog circuits, device physics, and process engineering.

• Qualify the product with innovative control measures to provide best in Class DPM and Cell reliability.

• Collaborate closely with Fab, NAND Technology, NAND Design, Product Development, System Development, and Quality/Reliability teams to develop solutions and enable shipment of high‑quality end products.

• Integrates AI-assisted tools and insights into daily work to improve efficiency, quality, or effectiveness, exercising sound judgment and complying with organizational standards and legal requirements.

• Contributes to a culture of continuous improvement by identifying, testing, and sharing AI-enabled enhancements within one’s scope of work.

• Ability to apply baseline digital fluency and role‑appropriate AI literacy to use AI‑enabled tools responsibly and effectively for research, analysis, content creation, problem‑solving, operational tasks, and achieving business outcomes.

• Support customer inquiries and provide technical insights related to product reliability.

• Drive strategic initiatives to enhance the overall reliability program and influence the direction of future product development.

Qualifications And Skills:

• Bachelor’s degree  or Master’s degree  with of relevant experience in Electrical Engineering or related field

• Knowledge in Semiconductor Reliability, NAND Technology, and Electrical Failure Analysis.

• Understanding in Design, Device Physics, Circuits,  Process.

• Strong statistical analysis, communication, and problem‑solving skills.

• Experience with application of AI tools, LLMs ,  data analysis tools (e.g., Python, JMP, Tableau).

• Strong analytical and problem‑solving skills.

• Team player and self driver.

Why Micron

Micron is a global leader in memory and storage technology, delivering HBM,DRAM, NAND,  and NOR solutions that power the world’s data‑driven AI innovation. At Micron, you’ll work on technology that matters—alongside teams that value ownership, learning, and technical excellence.

Manages production support engineering for a specific product or group of products after transfer from design to high volume production. Interfaces with design, process, test and reliability engineering to solve problems. Sustains products with cost reduction and yield improvements.

5 days, 8.30am to 5.50pm

Salary: $4000+/- (Engineer); $5500+/- (Senior Engineer)

Location: Bedok 

Job scope:

• Lead the design and development of PLC, SCADA, and control systems (e.g., Siemens, Rockwell, Schneider)
• Integrate hardware and software systems across multiple platforms
• Conduct Factory Acceptance Tests (FAT) and Site Acceptance Tests (SAT)
• Support site installation, commissioning, and system troubleshooting
• Collaborate closely with Project Managers, clients, and vendors
• Prepare and review engineering documentation and reports
• Prepare system architecture, control philosophies, and functional design specifications
• Design control panels, wiring diagrams, and I/O lists
• Ensure compliance with client specifications, industry standards, and regulatory requirements
• Configure communication protocols (e.g., Modbus, Profibus, Ethernet/IP, OPC)
• Perform software integration between various subsystems and third-party equipment
• Conduct internal testing and debugging of control systems
• Monitor engineering progress and ensure timely delivery of deliverables
• Coordinate with vendors, subcontractors, and clients on technical matters
• Propose improvements in system design, engineering practices, and workflows
• Mentor junior engineers and provide technical leadership

Requirements:

• Degree in Electrical Engineering, Automation, Mechatronics, or related field
• 5–8 years of experience in system integration / industrial automation
• Strong hands-on experience in PLC/SCADA programming and commissioning
• Familiar with industrial communication protocols (Modbus, Profibus, Ethernet/IP, OPC)
• Experience in control panels and instrumentation systems
• With valid class 3/3A license 

Kelly Chong Reg No:R26161160

The Supreme HR Advisory Pte Ltd EA No: 14C7279

We are seeking an expert Senior AI Infrastructure & Networking Engineer to lead the architecture, deployment, and optimization of our next-generation AI Factory. In this role, you will be responsible for building and scaling high-density GPU supercomputing clusters (up to 512+ nodes) featuring NVIDIA Blackwell UltraB300 systems. You will bridge the gap between heavy physical infrastructure (liquid cooling/busbar power) and advanced logical fabrics, ensuring predictable, line-rate, and lossless transport for massive generative AI training and reasoning workloads.

Key Responsibilities

• AI Fabric Architecture & Deployment: Design, build, and optimize high-throughput, ultra-low-latency East-West compute networks using NVIDIA Spectrum-X Ethernet platforms (Spectrum-4 ASICs) and/or NVIDIA Quantum-X800 InfiniBand switching.
• Performance Tuning for Lossless Networking: Configure and fine-tune critical Layer 2/3 lossless transport mechanisms, including Remote Direct Memory Access over Converged Ethernet (RoCE v2), Priority Flow Control (PFC), Explicit Congestion Notification (ECN), and DCQCN.
• Rail-Optimized Topologies: Implement and maintain non-blocking, multi-plane, full fat-tree network topologies mapped to 8-GPU server architectures to maximize collective communication performance via NCCL (NVIDIA Collective Communications Library).
• SmartNIC & DPU Management: Deploy and manage high-speed compute network interfaces, including ConnectX-8 SuperNICs (800 Gb/s) and BlueField-3 DPUs for isolated infrastructure management, storage acceleration, and multi-tenant security.
• Full-Stack Orchestration & Automation: Drive infrastructure-as-code deployments using Ansible and Terraform. Initialize and monitor the NVIDIA Network Operator within core Kubernetes orchestration layers.
• Telemetry & Validation: Utilize deep network telemetry tools such as NVIDIA NetQ and "What Just Happened" (WJH) to stream real-time switch diagnostics. Conduct line-rate cluster benchmarking using ib_write_bw and ib_write_lat to eliminate physical layer bottlenecks.
• Cross-Functional Infrastructure Alignment: Collaborate closely with data center facility teams on high-density environment metrics (~15–20 kW+ per rack, liquid-cooled rows, Coolant Distribution Units (CDUs), and Rear Door Heat Exchangers). Ensure operational verification aligns with international standards (e.g., IDCA G-Grade or Uptime Institute).

Required Technical Skills &Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Network Engineering, Systems Engineering, or a related technical discipline.
• AI Networking Expertise: Proven track record of configuring RoCE v2, adaptive routing, and traffic optimization specifically for machine learning/HPC workloads.
• Hardware Familiarity: Deep understanding of high-density scale-up and scale-out systems (NVIDIA HGX/DGX architectures, PCIe switching, OSFP/QSFP112 optical and copper assemblies).
• Software & Cluster Management: Experience with cluster deployment suites like NVIDIA Mission Control, Base Command Manager, Run:ai, or similar enterprise MLOps frameworks.
• Routing Protocols: Strong proficiency with advanced datacenter networking protocols, particularly eBGP IPv6 unnumbered underlays and EVPN/VXLAN overlays for multi-tenant isolation.
• Cabling & Layer 1 Validation: Experience managing complex structured fiber trunking (MPO-12/MPO-24 APC) and executing layer-1 diagnostics (ibdiagnet, iblinkinfo).

Preferred Certifications

• NVIDIA Certified Professional - AI Networking (NCP-AIN) (Highly Preferred)
• NVIDIA Certified Expert - Cloud End-to-End Fabric (NCE-CEF)
• Advanced networking tracks from major vendors (e.g., CCIE, JNCIE, or Nokia Service Routing Architect) combined with proven data center fabric experience.

What We Offer

• Opportunity to work with first-of-its-kind, world-class AI supercomputing technologies (NVIDIA Blackwell Ultra).
• High-impact role shaping the foundational architecture for enterprise generative AI and large-scale LLM initiatives.
• Competitive salary, comprehensive benefits package, and continuous learning paths for advanced AI operations certifications.

We are seeking an expert Senior AI Infrastructure & Networking Engineer to lead the architecture, deployment, and optimization of our next-generation AI Factory. In this role, you will be responsible for building and scaling high-density GPU supercomputing clusters (up to 512+ nodes) featuring NVIDIA Blackwell UltraB300 systems. You will bridge the gap between heavy physical infrastructure (liquid cooling/busbar power) and advanced logical fabrics, ensuring predictable, line-rate, and lossless transport for massive generative AI training and reasoning workloads.

Key Responsibilities

• AI Fabric Architecture & Deployment: Design, build, and optimize high-throughput, ultra-low-latency East-West compute networks using NVIDIA Spectrum-X Ethernet platforms (Spectrum-4 ASICs) and/or NVIDIA Quantum-X800 InfiniBand switching.
• Performance Tuning for Lossless Networking: Configure and fine-tune critical Layer 2/3 lossless transport mechanisms, including Remote Direct Memory Access over Converged Ethernet (RoCE v2), Priority Flow Control (PFC), Explicit Congestion Notification (ECN), and DCQCN.
• Rail-Optimized Topologies: Implement and maintain non-blocking, multi-plane, full fat-tree network topologies mapped to 8-GPU server architectures to maximize collective communication performance via NCCL (NVIDIA Collective Communications Library).
• SmartNIC & DPU Management: Deploy and manage high-speed compute network interfaces, including ConnectX-8 SuperNICs (800 Gb/s) and BlueField-3 DPUs for isolated infrastructure management, storage acceleration, and multi-tenant security.
• Full-Stack Orchestration & Automation: Drive infrastructure-as-code deployments using Ansible and Terraform. Initialize and monitor the NVIDIA Network Operator within core Kubernetes orchestration layers.
• Telemetry & Validation: Utilize deep network telemetry tools such as NVIDIA NetQ and "What Just Happened" (WJH) to stream real-time switch diagnostics. Conduct line-rate cluster benchmarking using ib_write_bw and ib_write_lat to eliminate physical layer bottlenecks.
• Cross-Functional Infrastructure Alignment: Collaborate closely with data center facility teams on high-density environment metrics (~15–20 kW+ per rack, liquid-cooled rows, Coolant Distribution Units (CDUs), and Rear Door Heat Exchangers). Ensure operational verification aligns with international standards (e.g., IDCA G-Grade or Uptime Institute).

Required Technical Skills &Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Network Engineering, Systems Engineering, or a related technical discipline.
• AI Networking Expertise: Proven track record of configuring RoCE v2, adaptive routing, and traffic optimization specifically for machine learning/HPC workloads.
• Hardware Familiarity: Deep understanding of high-density scale-up and scale-out systems (NVIDIA HGX/DGX architectures, PCIe switching, OSFP/QSFP112 optical and copper assemblies).
• Software & Cluster Management: Experience with cluster deployment suites like NVIDIA Mission Control, Base Command Manager, Run:ai, or similar enterprise MLOps frameworks.
• Routing Protocols: Strong proficiency with advanced datacenter networking protocols, particularly eBGP IPv6 unnumbered underlays and EVPN/VXLAN overlays for multi-tenant isolation.
• Cabling & Layer 1 Validation: Experience managing complex structured fiber trunking (MPO-12/MPO-24 APC) and executing layer-1 diagnostics (ibdiagnet, iblinkinfo).

Preferred Certifications

• NVIDIA Certified Professional - AI Networking (NCP-AIN) (Highly Preferred)
• NVIDIA Certified Expert - Cloud End-to-End Fabric (NCE-CEF)
• Advanced networking tracks from major vendors (e.g., CCIE, JNCIE, or Nokia Service Routing Architect) combined with proven data center fabric experience.

What We Offer

• Opportunity to work with first-of-its-kind, world-class AI supercomputing technologies (NVIDIA Blackwell Ultra).
• High-impact role shaping the foundational architecture for enterprise generative AI and large-scale LLM initiatives.
• Competitive salary, comprehensive benefits package, and continuous learning paths for advanced AI operations certifications.

We are seeking an expert Senior AI Infrastructure & Networking Engineer to lead the architecture, deployment, and optimization of our next-generation AI Factory. In this role, you will be responsible for building and scaling high-density GPU supercomputing clusters (up to 512+ nodes) featuring NVIDIA Blackwell UltraB300 systems. You will bridge the gap between heavy physical infrastructure (liquid cooling/busbar power) and advanced logical fabrics, ensuring predictable, line-rate, and lossless transport for massive generative AI training and reasoning workloads.

Key Responsibilities

• AI Fabric Architecture & Deployment: Design, build, and optimize high-throughput, ultra-low-latency East-West compute networks using NVIDIA Spectrum-X Ethernet platforms (Spectrum-4 ASICs) and/or NVIDIA Quantum-X800 InfiniBand switching.
• Performance Tuning for Lossless Networking: Configure and fine-tune critical Layer 2/3 lossless transport mechanisms, including Remote Direct Memory Access over Converged Ethernet (RoCE v2), Priority Flow Control (PFC), Explicit Congestion Notification (ECN), and DCQCN.
• Rail-Optimized Topologies: Implement and maintain non-blocking, multi-plane, full fat-tree network topologies mapped to 8-GPU server architectures to maximize collective communication performance via NCCL (NVIDIA Collective Communications Library).
• SmartNIC & DPU Management: Deploy and manage high-speed compute network interfaces, including ConnectX-8 SuperNICs (800 Gb/s) and BlueField-3 DPUs for isolated infrastructure management, storage acceleration, and multi-tenant security.
• Full-Stack Orchestration & Automation: Drive infrastructure-as-code deployments using Ansible and Terraform. Initialize and monitor the NVIDIA Network Operator within core Kubernetes orchestration layers.
• Telemetry & Validation: Utilize deep network telemetry tools such as NVIDIA NetQ and "What Just Happened" (WJH) to stream real-time switch diagnostics. Conduct line-rate cluster benchmarking using ib_write_bw and ib_write_lat to eliminate physical layer bottlenecks.
• Cross-Functional Infrastructure Alignment: Collaborate closely with data center facility teams on high-density environment metrics (~15–20 kW+ per rack, liquid-cooled rows, Coolant Distribution Units (CDUs), and Rear Door Heat Exchangers). Ensure operational verification aligns with international standards (e.g., IDCA G-Grade or Uptime Institute).

Required Technical Skills &Qualifications

• Education: Bachelor’s or Master’s degree in Computer Science, Network Engineering, Systems Engineering, or a related technical discipline.
• AI Networking Expertise: Proven track record of configuring RoCE v2, adaptive routing, and traffic optimization specifically for machine learning/HPC workloads.
• Hardware Familiarity: Deep understanding of high-density scale-up and scale-out systems (NVIDIA HGX/DGX architectures, PCIe switching, OSFP/QSFP112 optical and copper assemblies).
• Software & Cluster Management: Experience with cluster deployment suites like NVIDIA Mission Control, Base Command Manager, Run:ai, or similar enterprise MLOps frameworks.
• Routing Protocols: Strong proficiency with advanced datacenter networking protocols, particularly eBGP IPv6 unnumbered underlays and EVPN/VXLAN overlays for multi-tenant isolation.
• Cabling & Layer 1 Validation: Experience managing complex structured fiber trunking (MPO-12/MPO-24 APC) and executing layer-1 diagnostics (ibdiagnet, iblinkinfo).

Preferred Certifications

• NVIDIA Certified Professional - AI Networking (NCP-AIN) (Highly Preferred)
• NVIDIA Certified Expert - Cloud End-to-End Fabric (NCE-CEF)
• Advanced networking tracks from major vendors (e.g., CCIE, JNCIE, or Nokia Service Routing Architect) combined with proven data center fabric experience.

What We Offer

• Opportunity to work with first-of-its-kind, world-class AI supercomputing technologies (NVIDIA Blackwell Ultra).
• High-impact role shaping the foundational architecture for enterprise generative AI and large-scale LLM initiatives.
• Competitive salary, comprehensive benefits package, and continuous learning paths for advanced AI operations certifications.

The Senior Logistics & Operations Development Manager will play a key role in supporting the operational development and market growth of the company’s logistics and technical-related service offerings.

This position requires a highly experienced individual capable of managing operational logistics frameworks while supporting business development and marketing initiatives in a startup environment.

Key responsibilities include:

• Develop and implement operational frameworks for logistics and fulfilment activities.

• Support business development initiatives through operational planning and logistics capability development.

• Assist in operational marketing initiatives related to logistics and service deployment.

• Coordinate operational resources for logistics operations including fulfilment, sorting, delivery, and distribution activities.

• Support engineering-related business opportunities by bridging technical understanding with operational logistics execution.

• Work closely with management to identify opportunities for operational expansion and service deployment.

• Establish operational SOPs and systems to support scalable logistics operations.

• Liaise with vendors, operational partners, and stakeholders to ensure smooth deployment of logistics activities.

• Support startup growth initiatives including new service rollout and operational structuring.
  

  Preferred Competencies

  Logistics operations development

  Fulfilment & distribution planning

  Operational marketing support

  Technical business development

  Startup operations scaling

  Process design & SOP implementation

Position title : Senior TCB Application & Technical Sales Engineer

Location: Admirax St

Working Days:  5 Day A Week

Working hours : 9:00am - 6:00pm

Salary : SGD 7,000 – SGD 10,000/month (Based on experience and technical capability).

Responsibilities:

• Engage semiconductor customers to understand packaging roadmap, process requirements, throughput targets, yield and reliability challenges.

• Support technical sales activities and customer discussions.

• Benchmark competitor equipment and identify technology gaps.

• Translate customer requirements into internal equipment specifications.

• Develop and optimize TCB process parameters on TCB Equipments.

• Support advanced packaging applications including HBM, CoWoS, CoPoS, 2.5D Packaging, 3D Packaging and Chiplet Integration.

• Troubleshoot bonding issues such as non-wet, misalignment, voids, delamination and warpage.

• Conduct DOE and process characterization activities.

• Work closely with Mechanical, Software, Electrical, Motion and Vision teams.

• Define alignment accuracy, thermal performance, bond force profiles, throughput targets and process windows.

• Lead machine qualification, FAT and SAT activities.

• Act as the internal customer during machine development.

• Support customer buyoff and onsite qualification activities.

Requirements:

• Bachelor’s or Master’s Degree in Materials Science, Mechanical Engineering, Electrical Engineering, Semiconductor Engineering or related fields.

• 5–15 years of semiconductor packaging experience preferred.

• Hands-on experience in TCB, Flip Chip and Advanced Packaging.

• Experience in HBM / CoWoS / 2.5D / 3D packaging.

• Experience in OSAT, IDM or semiconductor equipment environments preferred.

• Experience with fluxless or N2 bonding environment is an advantage.

• Strong understanding of Thermo Compression Bonding (TCB), Flip Chip processes, thermal management, warpage control, alignment systems, vision systems, process qualification, SPC and yield analysis.

• Experience with DOE, statistical analysis tools, failure analysis workflows and semiconductor process characterization.