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Mlops Google Cloud Jobs (NOW HIRING)

E-Solutions, Inc.

Data Engineer - AI/ML

San Jose, CA · On-site

Cloud Platform: Hands-on experience with a major cloud provider, with a strong preference for Google Cloud Platform (Google Cloud Platform). MLOps: Solid understanding of MLOps principles and ...

MSR Cosmos

Google Cloud ML Engineer

Dallas, TX · On-site

$55.25 - $73.75/hr

Google Cloud ML Engineer- Vertex AI & CCAI Chat Virtual Agent Expert Location: Dallas, TX (Day1 ... Solid understanding and practical application of MLOps best practices for chatbot pipelines ...

QUANTUM TECHNOLOGIES LLC

MLOPS Engineer

Texas City, TX · On-site

$70/hr

Design and implement cloud solutions, build MLOps on cloud (AWS or Google Cloud Platform) Build CI/CD pipelines orchestration by GitLab CI, GitHub Actions, Flux, Kustomize, Circle CI, Airflow or ...

Hobbsnews

$250/hr

Lead end-to-end AI, data, and cloud transformation programs using Google Cloud AI services ... Deep understanding of scaling AI‑driven solutions, ethical AI, and MLOps practices for ...

KPMG

Director, AI, Data & Google Cloud

Austin, TX · On-site

Lead end-to-end AI, data, and cloud transformation programs using Google Cloud AI services ... Deep understanding of scaling AI-driven solutions, ethical AI, and MLOps practices for maintaining ...

Jobtailor

Senior MLOps Engineer

Menomonee Falls, WI · On-site

$150 - $200/hr

In-depth knowledge of cloud platforms, preferably Google Cloud Platform, particularly Vertex AI ... MLOps Practices * Google Cloud Platform * Machine Learning Model Deployment * CI/CD Pipelines

New

Cyber 1 Armor

Senior MLOps / LLMOps Engineer

Milpitas, CA · On-site

$119K - $163K/yr

Strong hands-on experience with Databricks and MLflow Experience building and maintaining MLOps/LLMOps platforms Cloud expertise in Azure and/or Google Cloud Platform CI/CD pipeline development and ...

Credence

Senior Google AI Engineer

Mclean, VA

$105K - $145K/yr

As a Senior Google AI Engineer, you will serve as a handson technical leader for AI solution ... with Cloud Build and IaC. * Implement robust MLOps (experiment tracking, evaluation, bias ...

Credence

Senior Google AI Engineer

Mclean, VA · Remote

$107K - $146K/yr

We are growing our Google Cloud AI engineering capability to support our Department of War (DoW ... with Cloud Build and IaC. * Implement robust MLOps (experiment tracking, evaluation, bias ...

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Mlops Google Cloud information

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How much do mlops google cloud jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for mlops google cloud in the United States is $61.71, according to ZipRecruiter salary data. Most workers in this role earn between $54.09 and $74.04 per hour, depending on experience, location, and employer.

What is an MLOps engineer on Google Cloud?

An MLOps Engineer on Google Cloud is a professional responsible for managing the deployment, monitoring, and maintenance of machine learning models using Google Cloud Platform (GCP) services. They streamline the collaboration between data scientists and operations teams to automate and optimize the entire machine learning lifecycle. Their work includes setting up CI/CD pipelines for ML, managing infrastructure with tools like Vertex AI, and ensuring models are scalable, reproducible, and secure on Google Cloud.

What are some common challenges faced by MLOps engineers working with Google Cloud, and how can they be addressed?

MLOps engineers on Google Cloud often encounter challenges such as managing scalable infrastructure, integrating CI/CD pipelines for ML models, and ensuring secure deployment of services. Navigating the variety of tools within Google Cloud (like Vertex AI, Cloud Build, and BigQuery) can require extra learning time. Addressing these challenges involves staying updated with Google Cloud's best practices, leveraging automation for model training and deployment, and collaborating closely with data scientists and DevOps teams to ensure seamless workflows. Proactive communication and continuous learning are key to overcoming these hurdles.

What are the key skills and qualifications needed to thrive as an MLOps engineer specializing in Google Cloud, and why are they important?

To thrive as an MLOps Engineer on Google Cloud, you need a solid background in machine learning, cloud computing, and DevOps principles, typically supported by experience with Python and a relevant degree. Familiarity with Google Cloud Platform services like Vertex AI, BigQuery, Cloud Build, and CI/CD tools, as well as certifications such as Google Cloud Professional Machine Learning Engineer, are highly valuable. Strong problem-solving, collaboration, and communication skills help you work effectively with data scientists, engineers, and stakeholders. These skills ensure reliable deployment, scaling, and monitoring of ML models, which is critical for delivering robust, production-ready AI solutions.

What is the difference between Mlops Google Cloud vs Data Engineer?

AspectMlops Google CloudData Engineer
Required CredentialsGoogle Cloud certifications, ML and cloud skillsData engineering certifications, SQL, cloud platform knowledge
Work EnvironmentCloud-based, ML model deployment and managementData pipelines, ETL processes, database management
Industry UsageAI/ML projects on Google CloudData infrastructure across industries

While both roles involve cloud platforms, Mlops Google Cloud focuses on deploying and managing machine learning models, whereas Data Engineers build and maintain data pipelines and infrastructure. The roles often collaborate but have distinct skill sets and responsibilities within data and ML projects.

What other helpful pages are available for Mlops Google Cloud?

Other pages related to Mlops Google Cloud:

Infographic showing various Mlops Google Cloud job openings in the United States as of September 2026, with employment types broken down into 92% Full Time, 3% Part Time, and 5% Contract. Highlights an 76% Physical, 6% Hybrid, and 18% Remote job distribution, with an average salary of $128,365 per year, or $61.7 per hour.

Data Engineer - AI/ML

San Jose, CA • On-site

E-Solutions, Inc.
See more jobs at E-Solutions, Inc.external

Other

Posted 13 days ago

Job description

Title: Data Engineer - AI/ML

Location: San Jose, CA

Duration: 12+ Month Long-Term Contract -W2

GC-EAD,TN,OPT

Job Description

Required Qualifications
Experience: 3+ years of professional experience building and deploying machine learning models in a production environment.
Education: Bachelor's degree in Computer Science, Data Science, Statistics, or a related quantitative field.
Programming: Advanced proficiency in Python and its core data science/ML libraries (e.g., PyTorch, scikit-learn, Pandas).
Data & SQL: Advanced proficiency in SQL for complex data manipulation, aggregation, and analysis.
Generative AI: Demonstrable, hands-on experience in prompt engineering and/or fine-tuning Large Language Models (e.g., Gemini).
Cloud Platform: Hands-on experience with a major cloud provider, with a strong preference for Google Cloud Platform (Google Cloud Platform).
MLOps: Solid understanding of MLOps principles and experience with related tools (e.g., Vertex AI, CI/CD).
Preferred Qualifications (Nice-to-Haves):
Master’s or PhD in a relevant field.
Specific experience with Google Cloud Platform services like Vertex AI, BigQuery, Google Cloud Storage, and GKE.
Experience building RAG systems from the ground up.
Proven ability to lead technical projects and mentor other engineers.

Data Engineer - AI/ML2Python,Data Engineer,Gemini,("MACHINE LEARNING" OR MLOPS),("GOOGLE CLOUD" OR Google Cloud Platform)N/AW-2,Other,Contract,Hourly,W2United States

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