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Google Cloud Machine Learning Engineer Jobs in California

Compunnel

Machine Learning Engineer

San Jose, CA · On-site

Job Summary The Machine Learning Engineer will lead the development of advanced Machine Learning ... Deploy and manage machine learning models using AWS cloud technologies and SageMaker. * Translate ...

New

Pattern AI

Machine Learning Engineer

San Mateo, CA · On-site +1

Qualifications Experience: * 3+ years of professional experience as a Machine Learning Engineer or ... ML cloud services. * Familiarity with CNNs, RNN, LSTMs, and the latest research trends.

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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 Aug 13, 2026, the average hourly pay for google cloud machine learning engineer in California is $62.06, according to ZipRecruiter salary data. Most workers in this role earn between $52.88 and $70.67 per hour, depending on experience, location, and employer.

What is a Google Cloud Machine Learning engineer?

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?

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 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 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 the most commonly searched types of Google Cloud Machine Learning Engineer jobs in California?

The most popular types of Google Cloud Machine Learning Engineer jobs in California are:

What are popular job titles related to Google Cloud Machine Learning Engineer jobs in California?

For Google Cloud Machine Learning Engineer jobs in California, the most frequently searched job titles are:

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The top searched job categories for Google Cloud Machine Learning Engineer jobs in California are:

What cities in California are hiring for Google Cloud Machine Learning Engineer jobs?

Cities in California with the most Google Cloud Machine Learning Engineer job openings:

Google Cloud Machine Learning Engineer jobs near you

Machine Learning Engineer

Recruiting from Scratch

San Francisco, CA • On-site

Full-time

Re-posted 26 days ago

Job description

Job Summary:
Recruiting from Scratch represents a dynamic and innovative company in the healthcare AI sector that is on a mission to transform healthcare operations through advanced machine learning. The Machine Learning Engineer will develop and optimize machine learning models to enhance healthcare operations and collaborate with cross-functional teams to integrate solutions into existing workflows.
Responsibilities:
• Develop and optimize machine learning models using Python, PyTorch, and TensorFlow to enhance healthcare operations.
• Collaborate with cross-functional teams to integrate machine learning solutions into existing workflows and systems.
• Conduct experiments and analyze data to improve model performance and accuracy.
• Implement best practices in machine learning and software engineering to ensure high-quality deliverables.
• Participate in code reviews and contribute to a culture of continuous improvement and innovation.
Qualifications:
Required:
• 3+ years of experience in machine learning engineering or a related field.
• Proficient in Python and experienced with frameworks such as PyTorch and TensorFlow.
• Strong understanding of machine learning algorithms and their applications in real-world scenarios.
• Experience in developing and deploying scalable machine learning models.
Preferred:
• Familiarity with healthcare data and understanding of industry-specific challenges.
• Experience with cloud platforms and deployment of machine learning solutions in production environments.
• Knowledge of data preprocessing and feature engineering techniques.
Company:
A recruiting agency working with technology companies to help them hire software engineers, data roles, product managers, and hardware. Founded in 2021, the company is headquartered in Albany, USA, with a team of 11-50 employees. The company is currently Early Stage.
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About Recruiting from Scratch

Sourced by ZipRecruiter

Recruiting from Scratch is a premier talent firm that focuses on placing the best product managers, software, and hardware talent at innovative companies. Our team is 100% remote and we work with teams across the United States to help them hire. We work with companies funded by the best investors including Sequoia Capital, Lightspeed Ventures, Tiger Global Management, A16Z, Accel, DFJ, and more.

Industry

Recruiting and staffing services

Company size

11 - 50 Employees

Headquarters location

New York, NY, US

Year founded

2021

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