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Google Cloud Machine Learning Engineer Jobs in Naperville, IL

Co-Sourcing Partners

GCP AI/ML Engineer

Chicago, IL · On-site

S. Role Overview We are seeking a talented and experienced GCP AI/ML Engineer to design, build, and operationalize scalable machine learning solutions on Google Cloud Platform (GCP). This role ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and ...

Crowe LLP

Machine Learning Engineer

Chicago, IL · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Crowe LLP

Machine Learning Engineer

Chicago, IL · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Socket.dev

Machine Learning Engineer

Chicago, IL · On-site

$62 - $100/hr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

New

TekCommands Inc

AWS + Generative AI Engineer

Chicago, IL · On-site

$66.75 - $87.50/hr

AWS Cloud & Machine Learning * AWS Bedrock & Generative AI * AWS Data Pipelines & Infrastructure ... Collaborate with data engineers, data scientists, and application teams to deliver AI-powered ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a ... cloud ML infrastructure (AWS, GCP, or Azure) Knowledge of handling large scale image data, data ...

Crowe LLP

Machine Learning Engineer

Chicago, IL · On-site

$62K - $100K/yr

As an AI Engineering team member, you will be instrumental in advancing new features and/or solutions from the Proof of Concept stage to full production readiness. Your role involves refining and ...

Google

Pursuit Lead III, Google Cloud

Chicago, IL · On-site

$15.75 - $20/hr

... 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 ...

Accenture

Google Data Specialist

Chicago, IL · On-site

$70K - $196K/yr

You Are A hands-on Specialist with foundational experience in Data Engineering, Analytics, or Machine Learning-now building deep expertise in Google Cloud Platform (GCP). You are eager to apply ...

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All JobsGoogle Cloud Machine Learning Engineer JobsGoogle Cloud Machine Learning Engineer Jobs in Naperville, IL

Google Cloud Machine Learning Engineer information

See Naperville, IL salary details

$23

$62

$87

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

As of Aug 20, 2026, the average hourly pay for google cloud machine learning engineer in Naperville, IL is $62.79, according to ZipRecruiter salary data. Most workers in this role earn between $53.51 and $71.54 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 Naperville, IL?

The most popular types of Google Cloud Machine Learning Engineer jobs in Naperville, IL are:

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

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Cities near Naperville, IL with the most Google Cloud Machine Learning Engineer job openings:

Google Cloud Machine Learning Engineer jobs near you

Machine Learning Engineering Manager

United Airlines, Inc.

Chicago, IL • On-site

$118K - $141K/yr

Full-time

Posted 16 days ago

United Airlines rating

7.9

Company rating: 7.9 out of 10

Based on 342 frontline employees who took The Breakroom Quiz

7th of 26 rated airlines

Job description

Description
Job overview and responsibilities
Develops and programs integrated software algorithms to structure, analyze and leverage data in systems applications. Develops and communicates statistical modeling techniques to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy. Completes programming and implements efficiencies, performs testing and debugging. Completes documentation and procedures for installation and maintenance. Applies deep learning technologies to give computers the capability to visualize, learn and respond to complex situations. Can work with large scale computing frameworks, data analysis systems and modeling environments.
  • Design and implement key components of the Machine Learning Platform infrastructure and establish processes and best practices
  • Work cross-functionally with data scientists, data engineers, and IT teams to design, develop, deploy, and integrate high-performance, production-grade machine learning solutions and data intensive workflows
  • Partner with data scientists and data engineers to create and refine features from underlying data and build reproducible feature pipelines to train models and serve features in production
  • Partner with data platform and operations teams to solve complex data ingestion, pipeline and governance problems for machine learning solutions
  • Take ownership of production systems with a focus on delivery, continuous integration, and automation of machine learning workloads
  • Provide technical mentorship, guidance, and quality-focused code review to data scientists and ML engineers

Qualifications
What's needed to succeed (Minimum Qualifications):
  • Bachelor's degree in computer science, engineering, or a related technical discipline
  • 3+ years of experience in managing technical teams and projects
  • 3+ years of experience in full software lifecycle development using Python
  • 3+ years of experience leading an ML Ops team familiar with large cloud environments, Big Data technologies
  • 3+ years in software development in Python, Java, PySpark
  • 3+ Years of Experience with Machine Learning and Machine Learning workflows
  • 3+ years of experience designing and developing using technologies as Docker, Kubernetes
  • Strong software engineering experience with Python and at least one additional language such as Java, Go, Rust, or C/C++
  • Understanding of machine learning principles and techniques
  • Experience with data science tools and frameworks (e.g. PyTorch, Tensorflow, Keras, Pandas, Numpy, Spark)
  • Experience designing and developing scalable cloud native solutions using technologies such as Docker and Kubernetes and serverless services such as AWS Lambda, EKS, ECS, Fargate
  • Experience building infrastructure-as-code templates (e.g. AWS CloudFormation) and cloud-native CI/CD pipelines using tools such as AWS CodePipeline
  • Experience building ETL pipelines and working with big data technologies (e.g. Hadoop, Spark, and serverless technologies such as EMR, Redshift, S3, AWS Glue, and Kinesis)
  • Knowledge of distributed systems as it pertains to compute and data storage
  • Strong desire to experiment with and learn new technologies and stay aligned with the latest community developments in ML Ops/Engineering and cloud native
  • Excellent oral and written communication skills. Ability to prepare high-quality presentation materials and explain complex concepts and technical materials to less-technical audiences
  • Must be legally authorized to work in the United States for any employer without sponsorship
  • Successful completion of interview required to meet job qualification
  • Reliable, punctual attendance is an essential function of the position

What will help you propel from the pack (Preferred Qualifications):
  • AWS Certified Solution Architect (Associate or Professional)
  • Experience working as a Machine Learning Engineer or Data Scientist building and productional machine learning solutions
  • Experience building real-time event-driven stream processing solutions with technologies such as Kafka, Flink, and Spark
  • Experience with GPU acceleration (e.g. CUDA and CuDNN)
  • Experience with Kubernetes

What United Airlines employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

United Airlines logo

About United Airlines

Sourced by ZipRecruiter

United Airlines is embarking on an exciting journey to become the best airline in aviation history. Our purpose, "Connecting People, Uniting the World," extends beyond transportation, emphasizing our commitment to uplift and create opportunities in the places we serve. With a global presence and diverse workforce, we value inclusivity and are dedicated to hiring tens of thousands of individuals across various roles. Our comprehensive benefits package, including perks like space available travel, parental leave, and 401k, aims to support your well-being and growth.

Industry

Aviation

Company size

10,000+ Employees

Headquarters location

Chicago, IL, US

Year founded

1926

Social media

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