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Remote Google Trainer Jobs (NOW HIRING)

Swift Hire LLC

Google Cloud AI Engineer

Dallas, TX · Remote

$57 - $76.25/hr

Google Google Cloud AI Engineer Remote Google Cloud AI Engineer for Partner Flex Role Overview We ... AI on Data Strategy Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless ...

HemonX

Google Media Buyer (Remote)

Johnson City, TN · Remote

$500/day

... a Google Ads Media Buyer to add to our rapidly growing team. You'll have the chance to work with ... training, as well as have growth potential in an idea-meritocracy. Are you a Digital Marketing ...

Adswerve, Inc

Sr. Director, Google Practice Lead

$150K - $200K/yr

Wage differential is based on training and experience. Our team of 250+ employees is spread out ... Monthly Remote Work Stipend * New Hire Office Equipment Reimbursement Adswerve is an Equal ...

Adswerve, Inc

Sr. Director, Google Practice Lead

OR · On-site +1

$150K - $200K/yr

Wage differential is based on training and experience. Our team of 250+ employees is spread out ... Monthly Remote Work Stipend * New Hire Office Equipment Reimbursement Adswerve is an Equal ...

Cnx

Principal Architect: Google Cloud CX Solutions

Remote in USA Job Summary: We are seeking a dynamic and experienced Principal Architect for the ... Develop real-time guidance systems using Gemini-powered Agent Assist for training and coaching and ...

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Remote Google Trainer information

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How much do remote google trainer jobs pay per hour?

As of Sep 15, 2026, the average hourly pay for remote google trainer in the United States is $31.24, according to ZipRecruiter salary data. Most workers in this role earn between $19.95 and $35.58 per hour, depending on experience, location, and employer.

What is the difference between Remote Google Trainer vs Remote Google Ads Specialist?

AspectRemote Google TrainerRemote Google Ads Specialist
CertificationsGoogle Certified Trainer, Google Workspace CertificationGoogle Ads Certification, Google Analytics Certification
Work EnvironmentOnline training sessions, webinars, workshopsCampaign management, ad creation, optimization
Industry UsageEducational institutions, corporate trainingDigital marketing agencies, e-commerce
Primary FocusTeaching Google tools and platformsManaging and optimizing ad campaigns

While both roles involve Google tools, Remote Google Trainers focus on educating users about Google Workspace and related platforms, whereas Remote Google Ads Specialists concentrate on creating and managing advertising campaigns. The certifications overlap but differ in application, and their work environments and industry usage reflect their distinct functions.

How to become a remote Google trainer?

To become a remote Google trainer, you typically need expertise in Google tools and certifications such as Google Workspace or Google Cloud certifications. Experience in training, strong communication skills, and familiarity with online teaching platforms are also important. Applying to Google or authorized training programs and demonstrating relevant skills can help secure such roles.
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Remote Google Trainer jobs near you
Infographic showing various Remote Google Trainer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 85% Full Time, 9% Part Time, and 5% Contract. Highlights an 73% Physical, 4% Hybrid, and 23% Remote job distribution, with an average salary of $64,984 per year, or $31.2 per hour.

Google Cloud AI Engineer

Dallas, TX • Remote

Swift Hire LLC
See more jobs at Swift Hire LLCexternal

$57 - $76.25/hr

Contractor

Posted 5 days ago

Job description

Google

Google Cloud AI Engineer

Remote

Google Cloud AI Engineer for Partner Flex

Role Overview

We are seeking a highly skilled Artificial Intelligence Engineer. This role is pivotal in establishing Googleʼs Data Cloud as the essential foundation for the "agentic era". You will be responsible for designing and deploying sophisticated AI agents and grounding them in unique business data to ensure trust and operational efficiency.

Core Responsibilities

Agentic Design & Implementation

Develop intelligent agents using Vertex AI Agent Builder to automate complex business workflows.

Leverage the Agent Developer Kit (ADK) to build and manage multi-agent systems that collaborate to solve end-to-end business challenges.

Implement tools like MCP (Model Context Protocol) Toolbox to securely connect agents to enterprise databases like BigQuery and Spanner.

AI on Data Strategy

Utilize Vertex AI for model training, tuning, and deployment, ensuring seamless integration with BigQuery for feature engineering.

Build and optimize streaming data pipelines (e.g., via Dataflow) to execute real-time inference using RunInference API or Vertex AI endpoints.

Ground AI models in live business context using vector engines within BigQuery or AlloyDB to eliminate "AI amnesia".

Operational Excellence (Soft Skills)

Active Participation: Show up promptly for all internal and client-facing meetings.

Transparent Communication: Provide regular, structured status updates to team members and stakeholders regarding project milestones and technical blockers.

Proactive Collaboration: Demonstrate the ability to ask for help when facing technical hurdles and contribute to a collaborative troubleshooting environment.

Consultative Approach: Navigate corporate environments to translate high-level business goals into robust technical architectures.

Technical Qualiffications

Vertex AI Mastery: Proven experience with Model Garden, Vertex AI Pipelines, and model evaluation.

Data Proficiency: Advanced knowledge of SQL for BigQuery, Python for ML engineering, and data preprocessing techniques (scaling, encoding, imputation).

Cloud Infrastructure: Hands-on experience with Google Cloud Storage and Vertex AI endpoints.

Emerging Tech: Familiarity with stateful real-time processing and the latest innovations in agentic architectures.

Preferred Experience

Background in financial services or retail to better understand industry-specific data logic (e.g., credit risk, royalty forecasting, or search relevance).

Knowledge of privacy and compliance standards for handling PII through masking and redaction.