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Google Cloud Machine Learning Engineer Jobs in Atlanta, GA

W2 Candidates Only We are seeking a Machine Learning Engineer to develop, deploy, and optimize ... processing, and cloud-based ML platforms. Required Skills: * 5+ years of Machine Learning ...

Google Gemini (multimodal reasoning, advanced RAG integration). * Meta LLaMA (fine-tuned/custom ... Leverage cloud ML platforms (AWS Sagemaker, Databricks ML) for experimentation and scaling.

Equifax is excited to add a Machine Learning Engineer to our team. What you'll do * Design complex ... Cloud Certification Strongly Preferred What could set you apart * Application Development ...

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Google Cloud Machine Learning Engineer information

See Atlanta, GA salary details

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$83

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

As of Sep 8, 2026, the average hourly pay for google cloud machine learning engineer in Atlanta, GA is $60.48, according to ZipRecruiter salary data. Most workers in this role earn between $51.54 and $68.89 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 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 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 the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Atlanta, GA?

The most popular types of Google Cloud Machine Learning Engineer jobs in Atlanta, GA are:

What job categories do people searching Google Cloud Machine Learning Engineer jobs in Atlanta, GA look for?

The top searched job categories for Google Cloud Machine Learning Engineer jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Google Cloud Machine Learning Engineer jobs?

Cities near Atlanta, GA with the most Google Cloud Machine Learning Engineer job openings:

Cloud Engineer, AI/ML, Global Services Delivery, Google Cloud

Google Inc.

Atlanta, GA • On-site

$150 - $200/hr

Other

Posted yesterday

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Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

48th of 247 rated software companies


Job description

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corporate_fare Google place Austin, TX, USA ; Atlanta, GA, USA ; +3 more ; +2 moreMid

Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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X Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Austin, TX, USA; Atlanta, GA, USA; Chicago, IL, USA; Addison, TX, USA.

  • Bachelor's degree in Computer Science or equivalent practical experience.
  • 6 years of experience building machine learning solutions and working with technical customers.
  • Experience coding in one or more general purpose languages (e.g., Python, Java, Go, C or C++) including data structures, algorithms, and software design.
  • Ability to travel up to 20% of the time.
Preferred qualifications:
  • Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience with data analytics, data visualization techniques and software, and deep learning frameworks.
  • Experience in agentic workflow or Large Language Model (LLM)-based solutions.
  • Experience in software development, professional services, solution engineering, technical consulting. Expertise in architecting and rolling out new technology and solution initiatives.
  • Experience with core data science techniques.
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments.
  • Knowledge of cloud computing, including virtualization, hosted services, multi-tenant cloud infrastructures, storage systems, and content delivery networks.
About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As a Cloud Engineer, you will play a key role in ensuring that strategic customers have the best experience moving to the Google Cloud machine learning (ML) suite of products. You will design and implement machine learning solutions for customer use cases, leveraging core Google products. You will work with customers to identify opportunities to transform their business with machine learning, and will travel to customer sites to deploy solutions and deliver workshops designed to educate and empower customers to realize the full potential of Google Cloud. You will have access to Google’s technology to monitor application performance, debug and troubleshoot product code, and address customer and partner needs. In this role, you will lead the timely execution of adopting the Google Cloud Platform solutions to the customer’s requirements.

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.

About the job

The Google Cloud Platform team helps customers transform and build what's next for their business — all with technology built in the cloud. Our products are developed for security, reliability and scalability, running the full stack from infrastructure to applications to devices and hardware. Our teams are dedicated to helping our customers — developers, small and large businesses, educational institutions and government agencies — see the benefits of our technology come to life. As part of an entrepreneurial team in this rapidly growing business, you will play a key role in understanding the needs of our customers and help shape the future of businesses of all sizes use technology to connect with customers, employees and partners.

As a Cloud Engineer, you will play a key role in ensuring that strategic customers have the best experience moving to the Google Cloud machine learning (ML) suite of products. You will design and implement machine learning solutions for customer use cases, leveraging core Google products. You will work with customers to identify opportunities to transform their business with machine learning, and will travel to customer sites to deploy solutions and deliver workshops designed to educate and empower customers to realize the full potential of Google Cloud. You will have access to Google’s technology to monitor application performance, debug and troubleshoot product code, and address customer and partner needs. In this role, you will lead the timely execution of adopting the Google Cloud Platform solutions to the customer’s requirements.

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: $152000 - $221000 (USD) + 15% bonus target + equity + benefits

Learn more about benefits at Google .

  • Work with customer technical leads, client executives, and partners to scope, manage and deliver successful implementations of cloud solutions becoming a trusted advisor to decision makers throughout the engagement.
  • Interact with sales, partners, and customer technical stakeholders to manage project scope, priorities, deliverables, risks/issues, and timelines for successful client outcomes.
  • Deliver effective big data and machine learning solutions and solve complex technical customer challenges.
  • Identify new product features and feature gaps, provide guidance on existing product challenges, and collaborate with product managers and engineers to influence the roadmap of Google Cloud Platform.
  • Deliver best practices recommendations, tutorials, blog articles, and technical presentations adapting to different levels of key business and technical stakeholders.

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 .

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.

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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