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Google Map Review Jobs in Raleigh, NC (NOW HIRING)

Facilitating client workshops and technical reviews and translating engineering detail into ... You will shape end-to-end solutions-from discovery and reference architecture mapping through ...

Braillist

Raleigh, NC · On-site

$14.75 - $19.50/hr

Google Apps; (or willing to learn) * Working knowledge of general classroom activities and routines ... maps, and diagrams for students with visual impairments. * Confers directly with Teacher of ...

Braillist

Raleigh, NC · On-site

$14.75 - $19.50/hr

Google Apps; (or willing to learn) Working knowledge of general classroom activities and routines ... maps, and diagrams for students with visual impairments. Confers directly with Teacher of Students ...

Revenue Operations Manager

Raleigh, NC · On-site

$116K - $145K/yr

... reviews. * Building out a comprehensive set of business performance dashboards to track Partner ... Expertise in Salesforce, Microsoft Excel, Google Sheets. * A detailed knowledge of processes and ...

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Google Map Review information

What is the difference between Google Map Review vs Local Business Owner?

AspectGoogle Map ReviewLocal Business Owner
Credentials/CertificationsNo formal credentials requiredBusiness license, permits, and certifications
Work EnvironmentOnline, remote, or on-site for review managementPhysical storefront or office
Employer/Industry UsageConsumers and users providing feedbackBusiness owners managing their reputation
Search/Comparison IntentLooking for reviews or feedback about a locationManaging business reputation and customer feedback

Google Map Review involves consumers or users leaving feedback about a business location on Google Maps. In contrast, a Local Business Owner manages and responds to reviews, overseeing their online reputation. While reviews are user-generated, business owners actively monitor and influence their online presence to attract customers.

What are the key skills and qualifications needed to thrive as a Google Maps Reviewer, and why are they important?

To thrive as a Google Maps Reviewer, you need strong attention to detail, familiarity with local geography, and proficiency in online research and data verification. Experience with mapping tools, content moderation systems, and sometimes crowd-sourced review platforms is typically important. Excellent written communication, critical thinking, and integrity help ensure accuracy in reviewing and reporting information. These skills are crucial for maintaining the quality and reliability of map data that users and businesses depend on daily.

What are Google Map Reviews?

Google Map Reviews are user-generated feedback and ratings left on Google Maps for businesses, landmarks, and other locations. These reviews help others decide where to go by providing insights into the experiences of past visitors. Businesses can also respond to reviews, which can enhance their reputation and customer relations. Leaving detailed, honest reviews contributes to the accuracy and usefulness of Google Maps.

What are some common challenges faced by Google Map Reviewers, and how can they effectively manage them?

Google Map Reviewers often encounter challenges such as verifying the accuracy of user-submitted information, dealing with conflicting data from multiple sources, and ensuring that reviews and edits comply with Google's content guidelines. To manage these challenges effectively, it's important to develop strong research skills, regularly reference Google's official guidelines, and communicate clearly with other team members or moderators when clarifications are needed. Staying organized and keeping up-to-date with platform changes can also help reviewers maintain accuracy and efficiency in their work.
What are popular job titles related to Google Map Review jobs in Raleigh, NC? For Google Map Review jobs in Raleigh, NC, the most frequently searched job titles are:
What job categories do people searching Google Map Review jobs in Raleigh, NC look for? The top searched job categories for Google Map Review jobs in Raleigh, NC are:
What cities near Raleigh, NC are hiring for Google Map Review jobs? Cities near Raleigh, NC with the most Google Map Review job openings:
HPC AI Solution Architect (S2S)

HPC AI Solution Architect (S2S)

Deloitte

Raleigh, NC • On-site

Other

Posted 20 days ago


Deloitte rating

8.1

Company rating: 8.1 out of 10

Based on 86 frontline employees who took The Breakroom Quiz

58th of 138 rated financial services


Job description

Lead Cloud HPC- AI Infrastructure Architect(S2S)

As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team in Deloitte's AI & Engineering practice, you will design and drive deployment of fully integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure in close partnership with Deloitte AI specialists and our ecosystem partners. You will shape end-to-end solutions-from discovery and reference architecture mapping through sizing and implementation.  You will partner with Sales Executives, AI application specialists, delivery engineering, and managed services to help clients achieve measurable outcomes from private AI assets. You will lead technical solution strategy for pursuits and active opportunities and translate complex client needs into clear, complete solutions and delivery requirements.

Recruiting for this role ends on 6/26/2026.


Work you'll do
As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team, you will be responsible for:

  • Leading architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design
  • Creatively defining reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software and operations
  • Driving architecture trade-offs and decisions across performance, scalability, reliability, locality, total cost of ownership, time-to-value, and risk
  • Owning the technical solution strategy in proposals and RFPs, including architecture narrative, assumptions, dependencies, sizing guidance, and delivery approach
  • Facilitating client workshops and technical reviews and translating engineering detail into executive-ready communications
  • Architecting complex, innovative technology solutions with a focus on business outcomes, cost of quality, and long-term scalability and sustainability.
  • Engaging with C-Suite client leadership during sales and delivery, including leading technical pre-sales discussions, shaping proposals, and supporting the closing of new business opportunities
  •  Supporting go-to-market strategies, including participation in industry events, conferences, and client briefings

The Team

The Silicon to Service team at Deloitte delivers end-to-end AI factories and advanced technology services that help organizations build, deploy, and operate large-scale, private AI and data platforms. We enable the next phase of enterprise AI adoption through private AI economics with cloud-like ese of use.  Join this unique opportunity to work on innovative AI platforms and emerging technologies in the rapidly evolving AI market while solving complex enterprise problems for some of the world's largest organizations.


Qualifications

Required:

  • 10+ years of experience in infrastructure architecture or engineering for large-scale platforms including design, implementation, operations, and optimization.
  • 4+ years designing or delivering GPU-accelerated platforms for AI, ML, or high-performance computing
  • 3+ years Linux system administration in production environments
  • 3+ years designing or operating distributed compute clusters for AI/HPC in hybrid cloud setups, including multi-GPU topologies, partitioning, scheduler integration, and scalability for edge-to-cloud workloads.
  • 2+ years with high-performance networking or storage for AI/HPC
  • 2+ years building containerized platforms using Kubernetes or Red Hat OpenShift, including GPU operators/drivers, CUDA container runtime, and cluster lifecycle automation
  • 2+ years automating infrastructure as code(IaC) with tools like Terraform and Ansible
  • At least 2 end-to-end deployments of reference architectures in the cloud or on-prem, including variants with security controls, network segmentation, operational runbooks, and validation testing
  • Experience in pre-sales or sales engineering, including discovery, solution demonstrations, and proposal/RFP contributions
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • 2+ years implementing AI/HPC cluster scheduling  (Slurm and Kubernetes), including multi-tenant queues, quotas, and GPU-aware policies
  • 2+ years supporting generative AI infrastructure patterns, including multi-node distributed training
  • Experience with AI agents and frameworks
  • Experience with high-throughput storage for AI/HPC
  • Experience executing NVIDIA co-sell motions with OEMS (Dell, HPC, Lenovo), CSPs ( AWS, Azure, Google Cloud), or independent software vendors ( Run:ai, OpenShift, Weights & Biases)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $141,200 to $278,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Qualifications:

Lead Cloud HPC- AI Infrastructure Architect(S2S)

As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team in Deloitte's AI & Engineering practice, you will design and drive deployment of fully integrated architectures for GPU-accelerated AI factories and high-performance computing infrastructure in close partnership with Deloitte AI specialists and our ecosystem partners. You will shape end-to-end solutions-from discovery and reference architecture mapping through sizing and implementation.  You will partner with Sales Executives, AI application specialists, delivery engineering, and managed services to help clients achieve measurable outcomes from private AI assets. You will lead technical solution strategy for pursuits and active opportunities and translate complex client needs into clear, complete solutions and delivery requirements.

Recruiting for this role ends on 6/26/2026.


Work you'll do
As a Lead Cloud Integrated Infra Engineer on the Silicon2Service team, you will be responsible for:

  • Leading architecture for pursuits and active opportunities, including discovery, requirements, constraints, and target-state design
  • Creatively defining reference architectures for on-premises, cloud, and hybrid GPU platforms across compute, network, storage, security, software and operations
  • Driving architecture trade-offs and decisions across performance, scalability, reliability, locality, total cost of ownership, time-to-value, and risk
  • Owning the technical solution strategy in proposals and RFPs, including architecture narrative, assumptions, dependencies, sizing guidance, and delivery approach
  • Facilitating client workshops and technical reviews and translating engineering detail into executive-ready communications
  • Architecting complex, innovative technology solutions with a focus on business outcomes, cost of quality, and long-term scalability and sustainability.
  • Engaging with C-Suite client leadership during sales and delivery, including leading technical pre-sales discussions, shaping proposals, and supporting the closing of new business opportunities
  •  Supporting go-to-market strategies, including participation in industry events, conferences, and client briefings

The Team

The Silicon to Service team at Deloitte delivers end-to-end AI factories and advanced technology services that help organizations build, deploy, and operate large-scale, private AI and data platforms. We enable the next phase of enterprise AI adoption through private AI economics with cloud-like ese of use.  Join this unique opportunity to work on innovative AI platforms and emerging technologies in the rapidly evolving AI market while solving complex enterprise problems for some of the world's largest organizations.


Qualifications

Required:

  • 10+ years of experience in infrastructure architecture or engineering for large-scale platforms including design, implementation, operations, and optimization.
  • 4+ years designing or delivering GPU-accelerated platforms for AI, ML, or high-performance computing
  • 3+ years Linux system administration in production environments
  • 3+ years designing or operating distributed compute clusters for AI/HPC in hybrid cloud setups, including multi-GPU topologies, partitioning, scheduler integration, and scalability for edge-to-cloud workloads.
  • 2+ years with high-performance networking or storage for AI/HPC
  • 2+ years building containerized platforms using Kubernetes or Red Hat OpenShift, including GPU operators/drivers, CUDA container runtime, and cluster lifecycle automation
  • 2+ years automating infrastructure as code(IaC) with tools like Terraform and Ansible
  • At least 2 end-to-end deployments of reference architectures in the cloud or on-prem, including variants with security controls, network segmentation, operational runbooks, and validation testing
  • Experience in pre-sales or sales engineering, including discovery, solution demonstrations, and proposal/RFP contributions
  • Ability to travel 50%, on average, based on the work you do and the clients and industries/sectors you serve.
  • Limited immigration sponsorship may be available.

Preferred:

  • 2+ years implementing AI/HPC cluster scheduling  (Slurm and Kubernetes), including multi-tenant queues, quotas, and GPU-aware policies
  • 2+ years supporting generative AI infrastructure patterns, including multi-node distributed training
  • Experience with AI agents and frameworks
  • Experience with high-throughput storage for AI/HPC
  • Experience executing NVIDIA co-sell motions with OEMS (Dell, HPC, Lenovo), CSPs ( AWS, Azure, Google Cloud), or independent software vendors ( Run:ai, OpenShift, Weights & Biases)

The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $141,200 to $278,300.

You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.

Education:Bachelor's DegreeEmployment Type:

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