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Google Cloud Machine Learning Engineer Jobs in Ohio

Aivra Health LLC

$28 - $45/hr

Machine Learning Engineer Intern United States Internship | Full-Time (40 hours/week) Pay Range ... Google Cloud AI Platform * Docker * Kubernetes * MLflow * CI/CD pipelines * Model Deployment ...

Centraprise Corp

Google Gemini AI Architect

Cleveland, OH · On-site

$61 - $80.25/hr

Google Cloud Professional Certifications, such as Professional Cloud Architect or Machine Learning Engineer. * Demonstratable experience on Google Cloud Platform * Verbal and written communication ...

AceStack LLC

Google Gemini AI Architect

Cleveland, OH · On-site

$161K/yr

Google Cloud Professional Certifications, such as Professional Cloud Architect or Machine Learning Engineer. • Demonstratable experience on GCP • Verbal and written communication skills Roles ...

New

Deloitte

AI Solutions Architect

Cincinnati, OH · On-site

$61.50 - $81/hr

... Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft Azure AI Engineer Associate, Microsoft Azure Data Scientist Associate, or Microsoft Azure Solutions ...

SCATR Corp.

Artificial Intelligence Engineer

Cleveland, OH · On-site

$111K - $133K/yr

We integrate with global providers like Amazon Web Services, Microsoft Azure, Google Cloud and ... The ideal candidate will have a strong background in AI, machine learning and data science, with ...

The Hartford

AI Machine Learning Engineer

Columbus, OH · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps ... Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and ...

Bespoke Labs

Machine Learning Engineer

Toledo, OH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Accenture

Google Cloud (AGBG) Sales Architect

Columbus, OH · On-site

$60.75 - $77.25/hr

To accelerate our customers transformation leveraging cloud, we combine world-class learning and ... Build a clear career pathway toward senior engineering, architecture, or leadership roles within a ...

Bespoke Labs

Machine Learning Engineer

Cleveland, OH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Bespoke Labs

Machine Learning Engineer

Columbus, OH · On-site

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post ... scale on cloud or HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology ...

Deloitte

AI Solutions Architect

Columbus, OH

$60.75 - $80.25/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

Deloitte

AI Solutions Architect

Cleveland, OH

$61 - $80.50/hr

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

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Google Cloud Machine Learning Engineer information

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How much do google cloud machine learning engineer jobs pay per hour?

As of Jun 27, 2026, the average hourly pay for google cloud machine learning engineer in Ohio is $59.79, according to ZipRecruiter salary data. Most workers in this role earn between $50.96 and $68.12 per hour, depending on experience, location, and employer.

What are Google Cloud Machine Learning Engineers?

Google Cloud Machine Learning Engineers are professionals who design, build, and deploy machine learning models using Google Cloud Platform (GCP) services and tools. They work with large datasets, develop scalable ML solutions, and collaborate with data scientists and software engineers. Their role often includes automating data pipelines, optimizing model performance, and ensuring the reliability and security of ML deployments on the cloud. These engineers have expertise in both machine learning algorithms and cloud infrastructure, making them key contributors to data-driven projects.

What are the key skills and qualifications needed to thrive as a Google Cloud Machine Learning Engineer, and why are they important?

To thrive as a Google Cloud Machine Learning Engineer, you need strong programming skills in Python or Java, a deep understanding of machine learning algorithms, and a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, TensorFlow, and relevant certifications like the Professional Machine Learning Engineer certification is highly valuable. Excellent problem-solving abilities, collaboration, and clear communication make someone stand out in this position. These skills and qualities are critical for designing, deploying, and optimizing scalable ML solutions that meet business objectives in cloud environments.

What is the salary of an aiml engineer in Google?

A Google Cloud Machine Learning Engineer typically earns a salary ranging from $120,000 to $180,000 annually, depending on experience, location, and level within the company. Compensation may also include bonuses, stock options, and benefits, with higher salaries often associated with advanced skills in cloud platforms and machine learning frameworks.

How much do machine learning engineers make at GCP?

Machine learning engineers at Google Cloud Platform (GCP) typically earn between $120,000 and $180,000 annually, depending on experience, location, and level. Salaries can increase with specialized skills in cloud services, data modeling, and certifications like Google Cloud Professional Machine Learning Engineer.

What is the difference between Google Cloud Machine Learning Engineer vs Data Scientist?

AspectGoogle Cloud Machine Learning EngineerData Scientist
Required CredentialsGoogle Cloud certifications, programming skills, ML knowledgeStatistics, data analysis, programming, often with advanced degrees
Work EnvironmentCloud platforms, coding, deploying ML modelsData analysis, modeling, reporting, often in research or business settings
Employer & Industry UsageTech companies, cloud service providers, enterprises using Google CloudVarious industries including finance, healthcare, marketing, research

Google Cloud Machine Learning Engineers focus on developing and deploying ML models on Google Cloud, requiring cloud certifications and coding skills. Data Scientists analyze data, build models, and generate insights, often with advanced degrees. While both roles work with data and ML, the Engineer role emphasizes cloud deployment and infrastructure, whereas Data Scientists focus on data analysis and modeling.

What engineers make $500,000?

Senior engineers in high-demand fields such as software development, data science, and machine learning can earn $500,000 or more annually, especially with extensive experience, specialized skills, and leadership roles. Roles like senior software engineers, machine learning engineers, and technical architects often reach this compensation level in large tech companies or through equity and bonuses.

Does Google hire machine learning engineers?

Yes, Google hires machine learning engineers to develop and implement AI and machine learning solutions across various products and services. These roles typically require expertise in programming, data analysis, and familiarity with tools like TensorFlow and Google Cloud Platform.

What are some typical cross-functional collaborations for a Google Cloud Machine Learning Engineer?

As a Google Cloud Machine Learning Engineer, you'll frequently work alongside data scientists, software engineers, and product managers to design, deploy, and maintain machine learning solutions at scale. Collaboration often involves translating business requirements into machine learning pipelines, integrating models into cloud-based applications, and ensuring that solutions are robust, secure, and scalable. Regular communication with DevOps and infrastructure teams is also common to optimize model deployment and monitor performance. This cross-disciplinary teamwork is crucial for delivering impactful, production-ready AI solutions.
What are popular job titles related to Google Cloud Machine Learning Engineer jobs in Ohio? For Google Cloud Machine Learning Engineer jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Google Cloud Machine Learning Engineer jobs in Ohio look for? The top searched job categories for Google Cloud Machine Learning Engineer jobs in Ohio are:
What cities in Ohio are hiring for Google Cloud Machine Learning Engineer jobs? Cities in Ohio with the most Google Cloud Machine Learning Engineer job openings:
Google Cloud Machine Learning Engineer jobs near you

Machine Learning Engineer Intern

Aivra Health LLC

On-site

$28 - $45/hr

Other

Posted 9 days ago

Job description

Machine Learning Engineer Intern

United States
Internship | Full-Time (40 hours/week)
Pay Range: $28 – $45 per hour 
Visa: H1B Sponsorship Available | STEM OPT, OPT & CPT Candidates Welcome

Position Overview

We are seeking a highly motivated Machine Learning Engineer Intern to join our AI/ML team. This role is ideal for students or entry level candidates in STEM fields who are passionate about building scalable machine learning models and deploying them into production environments.

The intern will work closely with Data Scientists and Software Engineers to develop, train, evaluate, and deploy machine learning models that solve real-world business problems.

Key Responsibilities

  • Assist in building and training machine learning and deep learning models

  • Perform data preprocessing, feature engineering, and exploratory data analysis (EDA)

  • Implement supervised and unsupervised learning algorithms

  • Optimize model performance using hyperparameter tuning

  • Deploy ML models using REST APIs or cloud services

  • Work on model monitoring, validation, and performance tracking

  • Collaborate with cross-functional teams in Agile/Scrum environment

  • Document experiments and maintain reproducible ML workflows

Required Qualifications

  • Currently pursuing or recently completed a Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, Statistics, Mathematics, or related STEM field

  • Strong understanding of Machine Learning fundamentals

  • Knowledge of Probability, Statistics, and Linear Algebra

  • Basic understanding of Data Structures and Algorithms

Technical Skills (ATS Keywords)Programming Languages

  • Python

  • R (preferred)

  • Java (basic knowledge)

  • SQL

Machine Learning & AI Frameworks

  • Scikit-learn

  • TensorFlow

  • Keras

  • PyTorch

  • XGBoost

  • LightGBM

Data Processing & Big Data

  • Pandas

  • NumPy

  • Apache Spark

  • PySpark

  • Hadoop

NLP & Advanced Techniques (Preferred)

  • Natural Language Processing (NLP)

  • Computer Vision

  • Deep Learning

  • Transformers

  • LLM fundamentals

Cloud & MLOps

  • AWS (SageMaker, S3, EC2)

  • Microsoft Azure ML

  • Google Cloud AI Platform

  • Docker

  • Kubernetes

  • MLflow

  • CI/CD pipelines

  • Model Deployment & Monitoring

Tools & Concepts

  • Git

  • REST APIs

  • Feature Engineering

  • Model Evaluation Metrics

  • A/B Testing

  • Agile/Scrum

Preferred Qualifications

  • Prior ML internship or academic research experience

  • Experience deploying models into production

  • Knowledge of MLOps practices

  • Strong problem-solving and analytical skills

  • Good communication and teamwork abilities

Compensation & Benefits

  • Competitive hourly compensation ($28 – $45/hr)

  • Hands-on real-world AI/ML project experience

  • Mentorship from senior ML engineers

  • Opportunity for full-time conversion

  • H1B sponsorship support for eligible candidates

  • STEM OPT extension support

Equal Opportunity Employer

We are an Equal Opportunity Employer and encourage applications from diverse backgrounds, including international students and professionals requiring H1B sponsorship or STEM OPT support.

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