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Remote Google Cloud Machine Learning Engineer Jobs in Chicago, IL

Staff Cloud Security Engineer

Chicago, IL · 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 ...

... and Machine Learning solutions that solve complex business challenges. In this role, you will ... Experience with cloud-based AI services, including AWS, Azure, or Google Cloud Platform.

Senior ML Engineer

Chicago, IL · 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

See Chicago, IL salary details

$24

$64

$89

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

As of Aug 8, 2026, the average hourly pay for remote google cloud machine learning engineer in Chicago, IL is $64.78, according to ZipRecruiter salary data. Most workers in this role earn between $55.24 and $73.80 per hour, depending on experience, location, and employer.

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.

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 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.

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 are the most commonly searched types of Google Cloud Machine Learning Engineer jobs in Chicago, IL? The most popular types of Google Cloud Machine Learning Engineer jobs in Chicago, IL are:

Staff Cloud Security Engineer

NinjaTrader

Chicago, IL • On-site, Remote

$145K - $195K/yr

Full-time

Retirement, PTO

Re-posted 20 hours ago


Job description

What you'll do:

As a Staff Cloud Security Engineer, you are the most senior individual contributor responsible for the security of our cloud platform. You will set the technical direction for how we secure workloads across Google Cloud Platform (GCP), design our edge and perimeter defenses using Cloudflare and Google Cloud Armor, and build the guardrails that enable engineering teams to move quickly without compromising security.

This is a hands-on, high-impact individual contributor role. You will not manage people but will establish engineering standards across the organization, influence company-wide architecture decisions, and serve as the senior technical authority during security reviews and incidents.

In this role you will:

  • Own the cloud security architecture across our GCP environments, including IAM and least privilege design, VPC Service Controls, Organization Policy, Shared VPC, Workload Identity, KMS/encryption, and Security Command Center
  • Design, deploy, and tune edge and application-layer defenses using Cloudflare (WAF, DDoS Protection, Zero Trust/Access, Bot Management, Rate Limiting) and Google Cloud Armor (Security Policies, Adaptive Protection, Rate Limiting, and Global Load Balancer integration)
  • Lead threat modeling and security architecture reviews for new services and major platform changes while balancing business velocity with security risk
  • Build security guardrails as code through policy-as-code, secure Terraform modules, and CI/CD security controls so secure defaults become the path of least resistance
  • Advance cloud detection and response capabilities by partnering with the SOC and Incident Response teams on logging pipelines, Chronicle/SIEM detections, and cloud-native alerting
  • Serve as a senior technical responder during security incidents, including investigation, containment, remediation, and post-incident hardening
  • Partner with GRC and Compliance teams to translate regulatory requirements such as ISO, SOC 2, SOX, and similar frameworks into scalable technical controls and evidence
  • Mentor senior and mid-level engineers while raising the overall security maturity of the engineering organization
  • Represent Cloud Security during cross-functional planning, architecture reviews, and strategic initiatives
What you'll need:
  • 8+ years of experience in security engineering, including at least 5 years focused on cloud security in production environments
  • Deep hands-on expertise securing Google Cloud Platform environments, including IAM, networking, VPC Service Controls, Security Command Center, KMS, and Organization Policy
  • Demonstrated production experience with Cloudflare, including WAF, DDoS Protection, Zero Trust/Access, Bot Management, and Google Cloud Armor
  • Strong Infrastructure-as-Code experience using Terraform and securing CI/CD pipelines
  • Proficiency in at least one programming or scripting language such as Python or Go for automation and tooling
  • Experience securing workloads within regulated industries and familiarity with frameworks such as PCI DSS, SOC 2, ISO, SOX, or similar
  • Demonstrated technical leadership and the ability to influence engineering teams without direct authority
Bonus points for:
  • Google Professional Cloud Security Engineer, CISSP, GCP Professional Cloud Architect, or similar certifications
  • Experience securing GKE/Kubernetes environments and container or software supply chain security
  • Multi-cloud experience across AWS and Azure
  • Experience building detection engineering or threat hunting programs
  • Previous experience in fintech, payments, trading, or other highly regulated financial environments
Compensation:

The salary range for this role will be $145,000.00 - $195,000.00 USD. In addition, this position will also receive an annual target bonus of 12%. Bonus pay at NinjaTrader is based on individual performance (50%) as well as company/team performance (50%).

Salary and bonus earnings are only two components of the total compensation package offered by NinjaTrader. NinjaTrader offers a 401K plan through ADP under which the company will match up to 3.5% of employee contributions. Annual paid time off allowance accrues at a rate of 23 days per year plus seven paid holidays.

Location:

This role is based in Chicago, IL. We are not open to remote candidates for this role.

Hybrid:

For Chicago-based employees, we follow a hybrid work schedule: In-office Tuesday through Thursday, with remote work on Mondays and Fridays. In addition to these weekly remote days, we offer:

  • 20 additional flex remote days annually
  • 5 Company Wide Office-Optional weeks tied to major holidays