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Model Builder Jobs in Rhode Island (NOW HIRING)

GXO Logistics

Senior DevOps AI Platform Engineer

NC · On-site +1

$130K - $167K/yr

Design, build, and manage secure, repeatable CI/CD pipelines supporting AI platform infrastructure, platform services, agents, MCP servers, LiteLLM, Agent Gateway integrations, model-serving ...

GXO Logistics

Lead AI Application Security Engineer

NC · On-site +1

$59 - $78.75/hr

Evaluate, implement, and manage AI security tooling, including AI firewalls, prompt injection detection, runtime protections, model scanning, and AI security automation while supporting build-versus ...

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All JobsModel Builder JobsModel Builder Jobs in Rhode Island

Model Builder information

See Rhode Island salary details

$10

$30

$65

How much do model builder jobs pay per hour?

As of Aug 22, 2026, the average hourly pay for model builder in Rhode Island is $30.72, according to ZipRecruiter salary data. Most workers in this role earn between $18.61 and $38.37 per hour, depending on experience, location, and employer.

What is a model builder?

Model Builders are professionals who design, construct, and assemble scale models for various purposes such as architecture, engineering, film, or product design. They use materials like plastic, wood, metal, or foam to create detailed physical representations of objects or structures. Model Builders often work from blueprints or digital plans and require strong attention to detail and craftsmanship. Their work helps clients visualize projects, test designs, or create props for entertainment and marketing. Model building can be both a technical and artistic role, depending on the industry.

What are the key skills and qualifications needed to thrive as a model builder?

To thrive as a Model Builder, you need strong spatial awareness, attention to detail, and experience with scale modeling techniques, often supported by a background in design, architecture, or engineering. Familiarity with tools such as CAD software, 3D printers, hand tools, and materials like wood, plastic, or foam is typically required. Creativity, patience, and effective communication are vital soft skills for interpreting client requirements and solving construction challenges. These skills and qualities ensure the creation of accurate, visually compelling, and functional models that meet project specifications and client expectations.

What are typical collaboration practices for model builders working on large architectural projects?

Model Builders frequently collaborate with architects, engineers, and design teams to ensure that physical models accurately represent project specifications. Communication is key, as Model Builders must interpret technical drawings and provide feedback on constructability within the model. They also coordinate closely with other fabrication specialists, often participating in regular project meetings to address design changes or challenges. This collaborative approach helps ensure the final model meets both aesthetic and functional requirements, while also adhering to project timelines.

What is the difference between Model Builder vs Data Analyst?

AspectModel BuilderData Analyst
Required CredentialsTypically requires a degree in engineering, computer science, or related fields; certifications in modeling or simulation are a plusUsually requires a degree in statistics, mathematics, or related fields; certifications in data analysis or visualization are common
Work EnvironmentPrimarily in engineering, manufacturing, or simulation labs; often involves working with CAD or simulation softwareIn offices or remote settings; involves working with data visualization tools and statistical software
Employer & Industry UsageUsed in manufacturing, aerospace, automotive, and engineering firms for creating models and simulationsUsed across industries including finance, healthcare, marketing, and technology for analyzing data and generating insights

Model Builders focus on creating physical or digital models and simulations, often requiring engineering or technical backgrounds. Data Analysts interpret data to inform business decisions, requiring strong analytical skills. While both roles involve working with data and models, their tools, environments, and objectives differ significantly.

How much does a model builder make?

Model builders typically earn a median annual salary of around $50,000 to $70,000, depending on experience, industry, and location. Skilled model builders who work with advanced tools like CAD software or in specialized fields may earn higher wages, and those with certifications or extensive experience can see increased compensation.
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For Model Builder jobs in Rhode Island, the most frequently searched job titles are:

What job categories do people searching Model Builder jobs in Rhode Island look for?

The top searched job categories for Model Builder jobs in Rhode Island are:

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For Model Builder jobs in RI, the most frequently searched job titles are:

Model Builder jobs near you
Infographic showing various Model Builder job openings in Rhode Island as of August 2026, with employment types broken down into 57% Full Time, and 43% Contract. Highlights an 100% In-person job distribution, with an average salary of $63,896 per year, or $30.7 per hour.

Senior DevOps AI Platform Engineer

GXO Logistics

NC • On-site, Remote

$130K - $167K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Re-posted yesterday

GXO Logistics rating

7.2

Company rating: 7.2 out of 10

Based on 241 frontline employees who took The Breakroom Quiz

187th of 365 rated logistics

Job description

Continue to Grow with GXO.
At GXO, we know our greatest asset is people like you - energetic, innovative people of all experience levels and talents who make GXO a great place to work. Your career matters to us because your passion and excitement will help keep our company moving forward.
Senior DevOps AI Platform Engineer
Are you ready to take your career to the next level with a rapidly growing global company? As a Senior DevOps Platform Engineer, you will establish and scale the enterprise DevOps operating model for GXO's Agentic AI Platform. This role is responsible for building secure, automated, and scalable cloud platform capabilities that enable AI application delivery across Google Cloud Platform, Kubernetes, Terraform, and CI/CD ecosystems. You'll partner closely with Cloud Engineering, Platform Architecture, Security, and Product teams to drive developer productivity, platform reliability, and operational excellence. If you're looking for an opportunity to make a significant impact on enterprise AI infrastructure, join us at GXO.
Pay, benefits and more
We are eager to attract the best, so we offer competitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and the opportunity to participate in a company incentive plan.
What you'll do on a typical day
  • Establish the enterprise DevOps operating model for GXO's Agentic AI Platform, including CI/CD standards, branching strategies, release governance, environment promotion, deployment approvals, and operational handoff practices.
  • Design, build, and manage secure, repeatable CI/CD pipelines supporting AI platform infrastructure, platform services, agents, MCP servers, LiteLLM, Agent Gateway integrations, model-serving components, and supporting services.
  • Engineer, deploy, and operate Kubernetes-based platform capabilities on Google Kubernetes Engine (GKE), including deployment standards, Helm or Kustomize, autoscaling, network policies, workload identity, secrets management, ingress/egress, observability, and production runbooks.
  • Own Terraform infrastructure delivery by developing reusable modules, managing state, enforcing pull request controls, implementing policy guardrails, maintaining environment parity, detecting configuration drift, and promoting infrastructure across development, test, staging, and production environments.
  • Partner with the Principal Cloud Engineer to implement Google Cloud Platform foundations while leading day-to-day DevOps enablement, release engineering, Kubernetes operations, pipeline reliability, and developer experience.
  • Collaborate with the Principal Cloud AI Platform Architect to translate enterprise architecture standards, reference architectures, and architectural decision records (ADRs) into automated build, test, deployment, and operational processes.
  • Enable Phase 2 platform capabilities, including GKE-based open-source model serving, vLLM or comparable inference runtimes, scalable deployment patterns, model tiering infrastructure, and cost-governed platform operations.
  • Implement enterprise DevSecOps controls in partnership with Information Security, including vulnerability scanning, dependency scanning, container image hardening, Binary Authorization (or equivalent), secrets management, audit logging, and secure deployment gates.
  • Create standardized "paved road" developer workflows that enable engineers to provision environments, deploy AI agents, publish MCP services, test integrations, and promote code changes through approved automation.
  • Champion AI-assisted software engineering practices by enabling secure AI coding tools, automated testing, documentation generation, code review acceleration, pipeline diagnostics, and developer productivity improvements.
  • Build comprehensive observability across the platform through logs, metrics, traces, dashboards, alerts, SLOs, SLIs, deployment health monitoring, traceability, cost attribution, and operational readiness reporting.
  • Automate operational processes to reduce manual effort, improve incident response readiness, and maintain runbooks for releases, rollbacks, break-glass procedures, platform operations, and escalation processes.
  • Support secure integration between the AI platform and Snowflake-governed data access patterns through automated deployment, configuration, policy enforcement, and runtime observability.
  • Develop and maintain engineering documentation, including CI/CD standards, Terraform module guidance, Kubernetes operating procedures, release checklists, onboarding documentation, and operational runbooks.

What you need to succeed at GXO
At a minimum, you'll need
  • Bachelor's degree in computer science, Engineering, Information Technology, Cloud Computing, or a related technical field; equivalent hands-on experience may be considered.
  • Google Cloud Professional DevOps Engineer certification required.
  • Minimum of 8 years of platform engineering, DevOps, Site Reliability Engineering (SRE), infrastructure engineering, cloud engineering, or software delivery engineering experience.
  • Minimum of 5 years of hands-on Google Cloud Platform experience supporting production environments.
  • Deep expertise with Google Kubernetes Engine (GKE), including Kubernetes operations, workload identity, networking, autoscaling, ingress/egress, Helm or Kustomize, and production troubleshooting.
  • Expert-level experience developing and managing Terraform infrastructure, including reusable modules, state management, CI/CD integration, policy-as-code, infrastructure promotion, and drift management.
  • Strong experience designing and maintaining secure CI/CD pipelines using Cloud Build, GitHub Actions, GitLab CI, Azure DevOps, Jenkins, or similar platforms.
  • Experience implementing GitOps and DevSecOps practices, including code review automation, dependency scanning, container security, secrets management, signed artifacts, deployment approvals, and security guardrails.
  • Experience supporting cloud-native AI, machine learning, analytics, developer platform, or data platform workloads on Kubernetes and Google Cloud.
  • Ability to collaborate effectively with principal architects, cloud engineers, Information Security, product teams, and software developers to translate architectural vision into production-ready solutions.
  • Strong operational mindset with experience supporting incident response, root cause analysis, observability, production support, SLOs/SLIs, release readiness, and continuous operational improvement.
  • Excellent technical communication skills with the ability to develop engineering documentation, operating procedures, automation standards, and developer guidance.
  • Ability to influence engineering teams across a global matrix organization while driving adoption of modern DevOps and platform engineering practices.

It'd be great if you also have
  • HashiCorp Terraform Associate certification.
  • Certified Kubernetes Administrator (CKA) or Certified Kubernetes Application Developer (CKAD) certification.
  • Google Cloud Professional Cloud Architect, Cloud Security Engineer, or Machine Learning Engineer certifications.
  • Experience with AI platform technologies including LiteLLM, Agent Gateway, MCP servers, Vertex AI, Gemini, model routing, vLLM, or open-source model serving frameworks.
  • Experience enabling AI-assisted software development through secure coding assistants, automated testing, documentation generation, and developer productivity tooling.
  • Strong understanding of secure enterprise AI platform operations, cloud-native architecture, and scalable infrastructure automation.
  • Experience driving platform standardization, operational excellence, and developer enablement across large engineering organizations.
  • Self-starter with the ability to quickly establish credibility, operate independently, and make an immediate impact on the reliability, security, scalability, and velocity of enterprise AI platforms.

We engineer faster, smarter, leaner supply chains.
GXO is a leading provider of cutting-edge supply chain solutions to the most successful companies in the world. We help our customers manage their goods most efficiently using our technology and services. Our greatest strength is our global team - energetic, innovative people of all experience levels and talents who make GXO a great place to work.
We are proud to be an Equal Opportunity employer including Disabled/Veterans.
GXO adheres to CDC, OSHA and state and local requirements regarding COVID safety. All employees and visitors are expected to comply with GXO policies which are in place to safeguard our employees and customers.
All applicants who receive a conditional offer of employment may be required to take and pass a pre-employment drug test.
The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. All employees may be required to perform duties outside of their normal responsibilities from time to time, as needed. Review GXO's candidate privacy statement here.

What GXO Logistics employees say

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About GXO Logistics

Sourced by ZipRecruiter

GXO Logistics, located in Greenwich, CT, US, is a global leader in the logistics industry. Specializing in innovative supply chain management, it operates across various sectors including e-commerce, food and beverage, technology, and retail. The company has cemented a notable reputation for providing top-notch outsourcing solutions that equip businesses to respond to market changes quickly and efficiently. Originally part of XPO Logistics, GXO, officially separated and spun off as a unique corporation in 2021, taking with it decades of expertise and a robust client roster. Their mission is to propel businesses forward with cutting-edge logistics and transportation solutions while adhering to their core values of safety always, customer-centric, and inclusive.

Industry

Transportation and warehousing

Company size

10,000+ Employees

Headquarters location

Greenwich, CT, US

Year founded

2021

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