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Remote Google Cloud Machine Learning Engineer Jobs in Illinois

Staff Cloud Security Engineer

Chicago, IL ยท On-site +1

$145K - $195K/yr

You will set the technical direction for how we secure workloads across Google Cloud Platform (GCP ... We are not open to remote candidates for this role. Hybrid: For Chicago-based employees, we follow ...

Candidates with experience in machine learning, large language models (LLMs), AI agents, and ... Experience with cloud platforms such as AWS, Azure, or Google Cloud. * Experience with CI/CD ...

Sr Data Engineer (Remote)

Bolingbrook, IL ยท Remote

$102K - $140K/yr

... machine learning and agentic AI solutions on our GCP and Databricks platforms to enhance Ulta guest ... platforms like Google Cloud Platform and Databricks. * Build data engineering solutions on GCP ...

Sr Data Engineer (Remote)

Bolingbrook, IL ยท On-site +1

$102K - $140K/yr

... machine learning and agentic AI solutions on our GCP and Databricks platforms to enhance Ulta guest ... platforms like Google Cloud Platform and Databricks. * Build data engineering solutions on GCP ...

Sr Data Engineer (Remote)

Bolingbrook, IL ยท Remote

$102K - $140K/yr

... machine learning and agentic AI solutions on our GCP and Databricks platforms to enhance Ulta guest ... platforms like Google Cloud Platform and Databricks. * Build data engineering solutions on GCP ...

GCP Cloud Platform Engineer

Chicago, IL ยท On-site +1

$60 - $80/hr

This role is ideal for a hands-on engineer with strong migration experience who can work independently to build, manage, and optimize production-ready infrastructure in Google Cloud Platform. The ...

Senior ML Engineer

Chicago, IL ยท Remote

$180K - $240K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 180-240K USD plus benefits plus equity.

Showing results 21-40

Remote Google Cloud Machine Learning Engineer information

What does a remote Google Cloud machine learning engineer do?

A Remote Google Cloud Machine Learning Engineer designs, develops, and deploys machine learning models on Google Cloud Platform (GCP) from a remote location. They work with cloud-based tools and services such as TensorFlow, Vertex AI, BigQuery, and Dataflow to build scalable, production-ready ML solutions. Their responsibilities also include data preprocessing, model training and evaluation, and integrating ML solutions with other cloud services. Collaboration with data scientists, software engineers, and stakeholders is a key part of the role, ensuring that ML solutions meet business goals while leveraging the full capabilities of Google Cloud.

How does a remote Google Cloud machine learning engineer typically collaborate with cross-functional teams?

As a Remote Google Cloud Machine Learning Engineer, collaboration often happens through virtual meetings, shared documentation, and cloud-based development environments. You'll regularly interact with data scientists, software developers, and product managers to align machine learning solutions with business objectives. Clear communication and proactive updates are essential, as you may work across time zones and need to coordinate on project requirements, data pipelines, and model deployment strategies. Tools such as Google Meet, Slack, and shared code repositories like Git are commonly used to facilitate seamless teamwork.

What are the key skills and qualifications needed to thrive as a remote Google Cloud machine learning engineer, and why are they important?

To thrive as a Remote Google Cloud Machine Learning Engineer, you need expertise in machine learning algorithms, data analysis, and proficiency in programming languages like Python, along with a degree in computer science or a related field. Familiarity with Google Cloud Platform (GCP) services such as Vertex AI, BigQuery, and TensorFlow, as well as relevant certifications like Google Professional Machine Learning Engineer, is highly valued. Strong problem-solving skills, self-motivation, and effective remote communication set top performers apart in this role. These competencies are critical for building scalable ML solutions, collaborating remotely, and delivering impactful results using cloud technologies.

What is the difference between Remote Google Cloud Machine Learning Engineer vs Remote AWS Machine Learning Engineer?

AspectRemote Google Cloud Machine Learning EngineerRemote AWS Machine Learning Engineer
Required CredentialsGoogle Cloud certifications, Python, ML frameworksAWS certifications, Python, ML frameworks
Work EnvironmentGoogle Cloud Platform, GCP toolsAWS Cloud, AWS tools
Industry UsageTech, finance, healthcare using GCPTech, retail, finance using AWS
Search & Comparison IntentHigh overlap in cloud-based ML rolesSimilar roles in cloud ML, different platform

Both roles involve developing machine learning models in cloud environments, requiring cloud platform certifications and expertise in Python and ML frameworks. The main difference lies in the cloud platform used: Google Cloud vs AWS. Candidates should choose based on their platform familiarity and employer requirements.

What are the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Illinois?

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

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

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

Infographic showing various Remote Google Cloud Machine Learning Engineer job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Google Cloud Platform - Engineering Manager

Huntington

Downers Grove, IL โ€ข On-site, Remote

$93K - $189K/yr

Full-time

Medical, Life, Retirement, PTO

Re-posted 23 days ago


Job description

Description

Job Summary

The Cloud Engineering Manager provides technical leadership and people management for a team responsible for designing, building, and operating scalable, secure, and highly available cloud platforms. This role combines handsโ€‘on cloud architecture expertise, Infrastructure as Code, and DevSecOps practices with strong coaching, mentoring, and delivery leadership.

The Cloud Engineering Manager partners closely with application teams, security, and enterprise architecture to ensure cloud solutions align with organizational standards, targetโ€‘state architecture, and business outcomes.

Key Responsibilities

Technical Leadership & Architecture

  • Define and evolve cloud architecture standards, patterns, and reference implementations across public, private, and hybrid environments.
  • Lead the design and review of cloudโ€‘native solutions across IaaS, PaaS, and containerized platforms.
  • Ensure platforms and applications are designed for high availability, resilience, scalability, and disaster recovery.
  • Act as a subjectโ€‘matter expert for cloud networking, provisioning, automation, and platform services.
  • Evaluate new cloud services, tools, and architectural approaches, providing clear recommendations with tradeโ€‘offs.

Cloud Engineering & DevSecOps

  • Lead the adoption and governance of Infrastructure as Code using tools such as Terraform, ARM, CloudFormation, or equivalent.
  • Drive DevSecOps practices, including CI/CD pipelines, automated testing, security scanning, and policyโ€‘asโ€‘code.
  • Ensure secure handling of credentials, certificates, encryption, and key rotation.
  • Partner with security teams to embed riskโ€‘based controls and compliance into cloud platforms.
  • Partner with risk, security, compliance, and audit teams to support internal and external exams.
  • Guide costโ€‘efficient cloud usage, including monitoring, optimization, and financial transparency.

People Management & Mentorship

  • Manage, mentor, and develop a team of cloud platform and Site Reliability engineers.
  • Foster a culture of technical excellence, ownership, and continuous improvement.
  • Provide coaching, career development guidance, and regular performance feedback.
  • Build and maintain a highโ€‘performing, collaborative engineering team.

Strategy & Collaboration

  • Align cloud engineering initiatives with enterprise architecture and business strategy.
  • Partner with application, product, and infrastructure teams to support mergers, migrations, modernization, and new product delivery.
  • Communicate architectural decisions, standards, and roadmaps clearly to both technical and nonโ€‘technical stakeholders.
  • Contribute to the organizationโ€™s longโ€‘term cloud vision and platform roadmap.

Required Qualifications

  • Bachelorโ€™s degree in Computer Science, Engineering, or a related field (or equivalent experience).
  • 10+ years of experience across multiple IT disciplines such as cloud architecture, application development, infrastructure, or operations.
  • Handsโ€‘on experience designing and operating workloads on at least one major public cloud platform.
  • Strong experience with Infrastructure as Code and automated cloud provisioning.
  • Design and governance of reusable IaC modules published via private registries and consumed through CI/CD pipelines.
  • Experience leading or contributing to DevSecOps toolchains and practices.
  • Solid understanding of cloud networking, security, identity, and access management.
  • Proven ability to lead teams and influence across organizational boundaries.

Preferred Qualifications

  • Google Cloud Platform (GCP) as the primary cloud provider.
  • Terraform or OpenTofu as the standard Infrastructureโ€‘asโ€‘Code tools.
  • Harness Software Delivery Platform used for CI/CD, infrastructure provisioning.
  • GitHub as the primary source code repository.
  • Azure DevOps Services (ADO) boards, wiki, etc.
  • Cloud architecture or engineering certifications.
  • Experience in regulated or financialโ€‘services environments.
  • Knowledge of containers, Kubernetes, and serverless architectures.
  • Experience with application and infrastructure monitoring and observability tools.
  • Background in application modernization, migration strategies, or platform engineering.
  • Prior experience as a technical lead or engineering manager.

What Success Looks Like

  • Cloud platforms are reliable, secure, scalable, and easy for application teams to consume.
  • Engineering teams deliver faster through automation and standardized patterns.
  • Cloud costs, security posture, and operational health are transparent and wellโ€‘managed.
  • Engineers are growing, engaged, and aligned with the organizationโ€™s cloud strategy.


Exempt Status: (Yes = not eligible for overtime pay) (No = eligible for overtime pay)

Yes

Workplace Type:

Office

Our Approach to Office Workplace Type

Certain positions outside our branch network may be eligible for a flexible work arrangement. Weโ€™re combining the best of both worlds:  in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Compensation Range:

93,000.00 - 189,000.00 USD Annual

The compensation range represents the anticipated low and high end of the base compensation range for this position. Actual compensation will vary based on various factors including but not limited to location, experience, and education. โ€ฏColleagues in this position are also eligible to participate in an applicable incentive compensation plan. โ€ฏIn addition, Huntington provides a variety of benefits to colleagues, including health insurance coverage, wellness program, life and disability insurance, retirement savings plan, paid leave programs, paid holidays and paid time off (PTO). 

Huntington is an Equal Opportunity Employer.

Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters:  Huntington will not pay a fee for any placement resulting from the receipt of an unsolicited resume.  All unsolicited resumes sent to any Huntington colleagues, directly or indirectly, will be considered Huntington property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.