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Google Cloud Machine Learning Engineer Jobs in Naperville, IL

Paylocity

Machine Learning Engineer

Schaumburg, IL · On-site

Description: Paylocity is an award-winning provider of cloud-based HR and payroll software ... Machine Learning Engineer Position Overview Paylocity is growing its Machine Learning Engineering ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Description: Paylocity is an award-winning provider of cloud-based HR and payroll software ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

Description: Paylocity is an award-winning provider of cloud-based HR and payroll software ... Senior Engineer Machine Learning Position Overview Paylocity is growing its Machine Learning ...

Accenture

Google Cloud (AGBG) Sales Engineer

Chicago, IL · On-site

$57.50 - $76.75/hr

Accenture Google Business Group (AGBG) focuses on Cloud solutions leveraging Google's Cloud ... To accelerate our customers transformation leveraging cloud, we combine world-class learning and ...

Referrals Only

Lead Machine Learning Engineer

Chicago, IL

$105K - $139K/yr

Lead Machine Learning Engineers at Thoughtworks use modern architectures to develop end-to-end ... You have hands-on experience with on-premise and cloud services for building and deploying ML ...

Lessen

Machine Learning Engineer II

Chicago, IL · On-site

$108K - $136K/yr

Familiarity with pytorch, pandas and cloud platform like AWS, Azure and GCP * Prompt engineering experience * Experience using a machine learning framework e.g. scikit-learn, pytorch or similar

Lessen

Machine Learning Engineer II

Chicago, IL · On-site

$108K - $136K/yr

Familiarity with pytorch, pandas and cloud platform like AWS, Azure and GCP * Prompt engineering experience * Experience using a machine learning framework e.g. scikit-learn, pytorch or similar

Google

Delivery Executive, Google Cloud

Chicago, IL · On-site

Experience collaborating with channel partners, systems integrators, and third-party developers to ... About the job The Google Cloud Consulting Professional Services team guides customers through the ...

Accenture

Google Cloud (AGBG) Sales Architect

Chicago, IL · On-site

$67 - $85.25/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 ...

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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 Jul 31, 2026, the average hourly pay for google cloud machine learning engineer in Naperville, IL is $62.35, according to ZipRecruiter salary data. Most workers in this role earn between $53.12 and $71.01 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 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 Naperville, IL? The most popular types of Google Cloud Machine Learning Engineer jobs in Naperville, IL are:
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What cities near Naperville, IL are hiring for Google Cloud Machine Learning Engineer jobs? Cities near Naperville, IL with the most Google Cloud Machine Learning Engineer job openings:
Google Cloud Machine Learning Engineer jobs near you

AI Engineer, Advanced Solutions Lab, Google Cloud

Google

Chicago, IL • On-site

Full-time

Re-posted 6 days ago

Google rating

8.8

Company rating: 8.8 out of 10

Based on 101 frontline employees who took The Breakroom Quiz

50th of 241 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: Chicago, IL, USA; Atlanta, GA, USA; Austin, TX, USA.
Minimum qualifications:
  • Bachelor's degree in Engineering, Computer Science, a related field, or equivalent practical experience.
  • 6 years of experience coding with one or more programming languages (e.g., Java, C/C , Python).
  • 3 years of experience building production artificial intelligence (AI) and machine learning (ML) models or agentic solutions models for use cases (e.g., tabular data, images, video, speech, and unstructured text) with TensorFlow, Keras, JAX, Spark ML, or Scikit Learn.
  • Experience conducting data and machine learning (ML) technical training in a client-facing technical consulting role.
  • Experience architecting cloud solutions on Google Cloud Platform or other public cloud models.

Preferred qualifications:
  • Master's degree or PhD in Computer Science, Mathematics, or other quantitative field, or equivalent practical experience.
  • Experience in machine learning (ML).
  • Experience working in a technology area.
  • Experience taking on new material and delivering it to clients and students.
  • Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT, and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Hive).

About the job
The AI Engineer role within the Advanced Solutions Lab (ASL) focuses on delivering and evolving a sophisticated Machine Learning and Generative AI curriculum for global participants. Operating in an immersive environment, you will work directly with customers to apply innovative AI solutions to high-impact business challenges and specific industry use cases. You will lead the daily educational journey for participants while continuously improving the program by integrating internal Google expertise and recommending the best open-source frameworks and models. Beyond these core duties, you will actively participate in the broader Google ML community through research collaboration, engineering projects, and strategic initiatives that shape the future of AI.
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 - $222000 (USD) 15% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities
  • Drive the Advanced Solutions Lab by delivering content, identifying machine learning (ML) experts across Google to support specific sessions, and providing ongoing curriculum enhancements.
  • Lead and support customers' machine learning projects from framing to implementation in the Advanced Solutions Lab.
  • Design artificial intelligence (AI)/machine learning (ML) curriculum by analyzing market trends and customer needs, developing materials in collaboration with cross-functional Google experts.
  • Stay abreast of machine learning developments and network across the Google Cloud research community to provide Advanced Solutions Lab participants with up-to-date knowledge and opportunities for engagements with other machine learning experts.
  • Serve as a machine learning subject matter expert for Google Cloud Consulting, supporting activities like client-facing services, intellectual property (IP) development, public speaking, and running machine learning bootcamps.

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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