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For Companies At a Glance
- Tasks: Own the lifecycle of GPU compute platforms and collaborate with top hardware vendors.
- Company: Fast-growing AI infrastructure company focused on innovation and efficiency.
- Benefits: Competitive salary, equity, remote work, and rapid career growth.
- Why this job: Join us to shape the future of AI technology and make a real impact.
- Qualifications: 5+ years in data centre hardware and hands-on GPU experience required.
- Other info: Supportive culture that values collaboration and personal growth.
The predicted salary is between 36000 - 60000 ÂŁ per year.
We are a fast-growing GPU cloud engineered for AI, providing cost-effective, high-performance infrastructure for start-ups and large enterprises. Our mission is to eliminate the complexity of AI development by delivering powerful, reliable, and scalable compute—enabling customers to innovate faster and operate more efficiently. Our team thrives on ownership, innovation, and accountability. Here, transparency builds trust, and every team member is empowered to deliver excellence with urgency. Join us, and you’ll help build the technology powering the future of AI.
About the Role
We’re seeking a Hardware Specialist to own the lifecycle of our GPU compute platforms—from working with OEMs to define the right systems, to powering, cooling, racking, networking, and maintaining high-density GPU infrastructure in production. You’ll be the internal authority on NVIDIA GPU servers and surrounding data center hardware, and the primary liaison with vendors (Dell, Lenovo, etc.). Your work will directly influence performance, reliability, and our ability to scale.
What You’ll Do
- Collaborate with hardware vendors (Dell, Lenovo, SIs/channel partners) to translate workload requirements into server configurations and BOMs.
- Maintain deep awareness of NVIDIA’s data center GPU portfolio, HGX/DGX systems, NVLink/NVSwitch, NICs/DPUs, and related components.
- Produce accurate node and rack power budgets (typical/max) with A/B feed redundancy, PSU efficiency, and power-capping considerations.
- Specify PDUs (single/three-phase), breaker sizing, UPS integration, and downstream distribution.
- Validate power draw during burn-in and acceptance testing; track capacity vs. plan.
- Define and validate cooling approaches for high-density GPU racks (air-cooled and liquid-ready).
- Support designs using RDHx or direct-to-chip liquid cooling systems (CDUs, facility water specs, quick-disconnects, leak detection).
- Monitor thermal telemetry and configure inlet/outlet thresholds.
- Define and maintain golden profiles for BIOS/UEFI, BMC/iDRAC/iLO/XCC, NIC, NVMe, GPU, and switch OS firmware.
- Automate updates using Redfish/IPMI/CLI/Ansible (or similar).
- Tune BIOS settings (NUMA, C-states, PCIe bifurcation, SR-IOV, Above 4G, etc.) to optimize GPU workloads.
- Design and integrate host networking for AI/HPC clusters across Ethernet (RoCEv2/DCB/PFC/ECN) and/or InfiniBand.
- Specify NICs, optics, transceivers, and cabling; support LAG/LACP/MLAG/EVPN-VXLAN where appropriate.
- Define acceptance and burn-in processes (power/thermal soak, memory/disk tests, GPU diagnostics).
- Track inventory, spares, failure rates, and vendor SLA performance.
- Produce runbooks, rack elevations, wiring diagrams, firmware matrices, and change documentation.
- Partner with Security on secure boot/TPM, firmware signing, and chain-of-custody.
- Own data-erasure standards for decommissioning.
About You (Qualifications)
Required:
- 5+ years building and operating enterprise/x86 data center hardware.
- Hands‑on experience with GPU‑accelerated platforms.
- Proven vendor management experience with at least one major OEM (Dell, Lenovo, Supermicro, HPE, etc.).
- Expertise across:
- Cooling: air and liquid‑ready rack designs
- Rack layouts: elevations, space/weight planning, cabling standards
- Networking: InfiniBand/Ethernet for AI/HPC (RoCEv2, DCB/PFC, optics)
- Scripting/automation (Ansible, Python, shell)
Nice to Have
- Experience with NVIDIA DGX/HGX systems, NVLink/NVSwitch, MIG/vGPU.
- Familiarity with liquid cooling systems (CDU, RDHx), facility water chemistry, and thermal engineering.
- Background in AI/HPC cluster deployments.
What We Offer
- Highly competitive compensation (base + equity).
- Rapid career growth in one of the fastest‑growing AI infrastructure companies.
- A remote‑first, flexible work environment built on trust.
- Opportunities to push boundaries, innovate, and have meaningful ownership.
- Supportive, collaborative culture that puts people first.
Seniority level: Mid‑Senior level
Employment type: Full‑time
Job function: Data Infrastructure and Analytics
Hardware Engineer employer: asobbi
Contact Detail:
asobbi Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hardware Engineer
✨Tip Number 1
Network like a pro! Attend industry meetups, webinars, or tech conferences where you can connect with other hardware enthusiasts and professionals. Don’t be shy—introduce yourself and share your passion for GPU compute platforms!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those involving NVIDIA GPU servers or data centre hardware. This will give potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for interviews by brushing up on your knowledge of power and cooling requirements for high-density GPU racks. Be ready to discuss your hands-on experience and how you've tackled challenges in previous roles.
✨Tip Number 4
Apply through our website! We love seeing candidates who are genuinely interested in joining our team. Tailor your application to highlight your vendor management experience and expertise in GPU-accelerated platforms.
We think you need these skills to ace Hardware Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Hardware Engineer. Highlight your experience with GPU compute platforms and any relevant vendor management skills. We want to see how your background aligns with our mission!
Showcase Your Projects: Include specific projects where you've worked on high-density GPU infrastructure or similar technologies. We love seeing real examples of your work that demonstrate your expertise and problem-solving skills.
Be Clear and Concise: When writing your application, keep it straightforward. Use bullet points for key achievements and avoid jargon unless it's relevant. We appreciate clarity and want to understand your qualifications quickly!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to hear from you!
How to prepare for a job interview at asobbi
✨Know Your Hardware Inside Out
Make sure you have a solid understanding of GPU compute platforms, especially NVIDIA's offerings. Brush up on the specifics of their data centre GPUs, including HGX/DGX systems and NVLink/NVSwitch. Being able to discuss these in detail will show your expertise and passion for the role.
✨Showcase Your Vendor Management Skills
Prepare examples of your experience working with major OEMs like Dell or Lenovo. Be ready to discuss how you've translated workload requirements into server configurations and how you've managed vendor relationships effectively. This will demonstrate your ability to collaborate and communicate across teams.
✨Demonstrate Problem-Solving Abilities
Think of scenarios where you've had to define cooling approaches or power budgets for high-density GPU racks. Be prepared to explain your thought process and the outcomes. This will highlight your analytical skills and your ability to handle complex challenges.
✨Prepare for Technical Questions
Expect questions about scripting and automation tools like Ansible or Python. Brush up on your knowledge of network integration for AI/HPC clusters, as well as your experience with documentation and operational processes. Showing confidence in these areas will set you apart from other candidates.
