Data Center Hardware Specialist I, Google Cloud (Fixed-Term Contract)

Google LLC
United States
3 months ago
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Role details

Contract type
Temporary contract
Employment type
Full-time (> 32 hours)
Experience level
Experienced
Experience required
2 years minimum
Compensation
$126,000.0 - $181,000.0
Working hours
Regular working hours
Languages
English
Job source

Tech stack

Artificial Intelligence Bioinformatics Cloud Computing Linux Distributed Systems Virtual Private Networks (VPN) Systems Architecture Systems Integration Google Cloud Load Balancing High Performance Computing Pytorch
+7 more
Firewalls (Computer Science) Computer Equipment Kubernetes Information Technology Hardware Acceleration Machine Learning Operations Hardware Infrastructure

Job description

As a Hardware Specialist, you will lead the technical delivery of confidential compute projects for strategic customers. You will serve as the primary technical liaison between global clients, internal engineering teams, and internal operations. Your role involves maintaining complex on-prem and cloud-based environments, ensuring seamless integration of high-performance accelerators with enterprise-grade networking and storage to support the next-generation of mission-critical, data-intensive workloads.It’s an exciting time to join Google Cloud’s Go-To-Market team, leading the AI revolution for businesses worldwide. You’ll leverage Google’s brand credibility-a legacy built on inventing foundational technologies and proven at scale. We’ll provide you with the world’s most advanced AI portfolio, including frontier Gemini models, and the complete Vertex AI platform, helping you to solve business problems. We’re a collaborative culture providing direct access to DeepMind’s engineering and research minds, empowering you to solve customer challenges. Join us to be the catalyst for our mission, drive customer success, and define the new cloud era-the market is yours.

The US base salary range for this full-time position is $126,000-$181,000. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more aboutbenefits at Google (https://careers.google.com/benefits/) .

Responsibilities

  • Maintain and oversee the end-to-end deployment of large-scale accelerated compute clusters, acting as the lead technical advisor for confidential, enterprise infrastructure initiatives.
  • Work with customer technical leads, and client executives to manage and deliver successful implementations of technical solutions for high-density computing environments.
  • Collaborate with internal specialists, Product, and Engineering teams to package technical playbooks, best practices, and reference architectures for high-performance computing, influencing the roadmap for next-generation hardware and software integration.
  • Interact with Sales and partners to manage project scope, priorities, deliverables, risks and issues, and timelines for successful client outcomes.
  • Travel approximately 30% of the time for client engagements.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google’sApplicant and Candidate Privacy Policy (./privacy-policy) .

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See alsoGoogle’s EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC_KnowYourRights_10_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Requirements

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area., * Bachelor’s degree in Computer Science, Electrical Engineering, or a related technical field, or equivalent practical experience.

  • 3 years of experience in technical solution delivery and project management for enterprise infrastructure projects.
  • 2 years of experience in technical architecture, systems administration, or infrastructure delivery in cloud or on-prem environments.
  • Experience in hardware triage, diagnostics, and guiding repair workflows for server clusters and networks., * Master’s degree or PhD in Computer Science or Engineering.
  • Experience with end-to-end system architecture or accelerated computing hardware (e.g. Kubernetes, GKE, EKS, GPU workloads, or Linux-based distributed systems).
  • Experience with networking and system design of load balancers, firewalls, and VPN in architecting, developing and maintaining production-grade systems.
  • Experience in maintaining clusters of massive-scale model training using high-end hardware accelerators and AI/ML infrastructure frameworks such as JAX, PyTorch, or OpenXLA).

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