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Google Cloud Machine Learning Engineer Jobs in California

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.

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ... Explore and manipulate 3D point cloud & mesh data * Own the delivery of technical workstreams

Who We're Looking For As a Machine Learning Engineer in Delivery, you are a problem solver who ... Explore and manipulate 3D point cloud & mesh data * Own the delivery of technical workstreams

Showing results 21-40

Google Cloud Machine Learning Engineer information

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$23

$62

$86

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

As of Aug 10, 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 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:

Customer Engineer II, Applied AI, Google Cloud

Google

Mountain View, CA • On-site

$65.75 - $88/hr

Full-time

Posted 12 days ago


Google rating

8.9

Company rating: 8.9 out of 10

Based on 102 frontline employees who took The Breakroom Quiz

40th of 242 rated software companies


Job description

info_outline
X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Mountain View, CA, USA; Sunnyvale, CA, USA; New York, NY, USA.
Minimum qualifications:
  • Bachelor's degree in Computer Science, Mathematics, a related technical field, or equivalent practical experience.
  • 6 years of experience with cloud native architecture in a customer-facing or support role.
  • 2 years of experience with conversational AI technology.
  • Experience building or leveraging artificial intelligence solutions or ML APIs and developing applications utilizing AI methods or frameworks.
  • Experience engaging with, and presenting to, technical stakeholders and executive leaders.
  • Experience with development methodologies and modernizing legacy applications.

Preferred qualifications:
  • Experience with contact center technologies and platforms and building conversational applications.
  • Experience with building and using AI (e.g., ML APIs, Machine Learning templates, RAG, LLMs).
  • Experience in coding using Java, C , or Python.
  • Experience with document and image AI.
  • Passion for technology and innovation.

About the job
When leading companies choose Google Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use Google Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales Googlers by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to Google Cloud products.
In this role, you will partner with technical Sales teams as an Applied Artificial Intelligence subject matter expert to differentiate Google Cloud to our customers. You will help prospective and existing customers and partners understand the power of Google Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in Proofs of Concept, and troubleshoot any technical questions and roadblocks related to Google's first-party Generative Artificial Intelligence solutions for customer experience applications. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and present solutions on Google Cloud. You will have excellent technical, communication, and organizational skills.
You will be a part of a team of fellow Googlers working in an environment of respect and where we promote equal opportunities to succeed.
Google Cloud accelerates every organization's ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $148000 - $215000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities
  • Help prospective customers and partners understand the power of Google Cloud, explain technical features, help customers design architectures, and problem-solve any potential roadblocks.
  • Share in-depth artificial intelligence (AI) expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, Proof of Concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to Google Cloud.
  • Demonstrate the business value of Google Cloud applied artificial intelligence solutions that meet, enhance, and innovate for our enterprise customers.
  • Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution on Google Cloud.
  • Travel to customer sites, conferences, and other related events as required, acting as a public advocate for Google Cloud.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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