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Remote Google Machine Learning Engineer Jobs in Chicago, IL

Allied

Senior Machine Learning Engineer

Chicago, IL · On-site +1

$150K - $185K/yr

POSITION SUMMARY The Senior Machine Learning Engineer is responsible for designing, building, and ... Remote Here at Allied, we believe that great talent can thrive from anywhere. Our remote friendly ...

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 fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Adidev Technologies Inc

AI/ML

Chicago, IL · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Delta, Google, Apple, Spotify, US Bank, FedEx, and more. We're not just a software consulting ...

Career Renew

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.

Adidev Technologies

AI/ML

Des Plaines, IL · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Delta, Google, Apple, Spotify, US Bank, FedEx, and more. We're not just a software consulting ...

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All JobsGoogle Machine Learning Engineer JobsRemote Google Machine Learning Engineer JobsRemote Google Machine Learning Engineer Jobs in Chicago, IL

Remote Google Machine Learning Engineer information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

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

As of Jun 9, 2026, the average yearly pay for remote google machine learning engineer in Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 per year, depending on experience, location, and employer.

What is a Remote Google Machine Learning Engineer?

A Remote Google Machine Learning Engineer is a professional who designs, builds, and deploys machine learning models and artificial intelligence solutions, often using Google Cloud technologies, while working from a remote location. These engineers collaborate with cross-functional teams to solve complex business problems, optimize data pipelines, and improve model performance. Their responsibilities typically include data preprocessing, model selection, training, evaluation, and deployment, all while ensuring scalability and security. Working remotely allows them to contribute to projects from anywhere, leveraging cloud-based tools and collaboration platforms.

What are the key skills and qualifications needed to thrive as a Remote Google Machine Learning Engineer, and why are they important?

To thrive as a Remote Google Machine Learning Engineer, you need a strong background in computer science, mathematics, and machine learning algorithms, typically supported by a relevant degree and experience in building scalable models. Proficiency with tools such as TensorFlow, Python, Google Cloud Platform (GCP), and familiarity with distributed systems is essential. Excellent problem-solving, communication, and self-management skills are crucial for effective remote collaboration and innovation. These capabilities enable engineers to deliver impactful machine learning solutions while seamlessly integrating with global Google teams.

How do Remote Google Machine Learning Engineers typically collaborate with cross-functional teams while working from different locations?

Remote Google Machine Learning Engineers often use a combination of video conferencing, cloud-based collaboration tools, and shared code repositories to work closely with data scientists, product managers, and software engineers. Regular stand-up meetings, sprint planning sessions, and detailed documentation help ensure everyone is aligned and project milestones are met. Despite being remote, engineers are encouraged to proactively communicate progress, share insights, and participate in code reviews to maintain a strong team dynamic and drive successful project outcomes.
What are popular job titles related to Remote Google Machine Learning Engineer jobs in Chicago, IL? For Remote Google Machine Learning Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Google Machine Learning Engineer jobs in Chicago, IL look for? The top searched job categories for Remote Google Machine Learning Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Google Machine Learning Engineer jobs? Cities near Chicago, IL with the most Remote Google Machine Learning Engineer job openings:
Remote Google Machine Learning Engineer jobs near you
Infographic showing various Remote Google Machine Learning Engineer job openings in Chicago, IL as of June 2026, with employment types broken down into 75% Full Time, 19% Part Time, 2% Contract, and 4% Nights. Highlights an 86% Physical, 7% Hybrid, and 7% Remote job distribution, with an average salary of $132,651 per year, or $63.8 per hour.

Senior Machine Learning Engineer

Allied

Chicago, IL • On-site, Remote

$150K - $185K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Posted 8 days ago

Job description

POSITION SUMMARY
The Senior Machine Learning Engineer is responsible for designing, building, and deploying scalable machine learning systems that drive business impact. This role will partner closely with data scientists, AI Technical Product Owners, and engineering teams to integrate machine learning capabilities into real business processes. The emphasis is on operational excellence, scalability, and long-term maintainability rather than research and experimentation.
ESSENTIAL FUNCTIONS
  • Design and implement end to end machine learning pipelines that support data ingestion, feature generation, model training, validation, deployment, and monitoring.
  • Operationalize models in coordination with data scientists and ensure they run reliably with requisite alerts and monitoring in production environments.
  • Build reusable frameworks and patterns that reduce friction when deploying new models or updating existing ones.
  • Ensure pipelines are secure, auditable, and appropriate for use in regulated enterprise environments.
  • Own and evolve the MLOps toolchain that supports model versioning, artifact management, experiment tracking, and deployment workflows.
  • Implement continuous integration and deployment practices for machine learning systems.
  • Establish monitoring and alerting for model performance, data quality, drift, and system health.
  • Partner with cloud and platform teams to manage compute resources, cost controls, and environment configurations.
  • Work with application engineering teams to integrate machine learning outputs into downstream systems and user workflows.
  • Support real time and batch inference patterns depending on business needs.
  • Ensure that machine learning services meet performance, reliability, and availability expectations for production use.
  • Collaborate closely with data scientists to shape models that are production ready and operationally sustainable.
  • Provide guidance on feature engineering, model packaging, and performance tradeoffs from a deployment perspective.
  • Document standards, patterns, and best practices for building and operating machine learning systems.
  • Contribute to the maturation of the organization's overall AI and ML engineering discipline.
  • Other duties as assigned

EDUCATION
  • Bachelor's degree in Computer Science, Math, Statistics, or equivalent work experience required.

EXPERIENCE AND SKILLS:
  • 6+ years of strong experience building and operating machine learning systems in production environments.
  • Solid software engineering skills with Python and familiarity with modern ML frameworks such as PyTorch or TensorFlow.
  • Experience with data pipelines, workflow orchestration, and model deployment patterns.
  • Hands on experience with cloud platforms and managed ML services, with Azure, AWS, and/or Databricks experience preferred.
  • Understanding of MLOps concepts including model versioning, monitoring, testing, and lifecycle management.
  • Experience working with sensitive data in regulated industries such as healthcare or insurance is strongly preferred.
  • Ability to work cross functionally and translate between data science, engineering, and business stakeholders.

POSITION COMPETENCIES
  • Accountability
  • Analytical Problem Solving
  • Collaboration
  • Execution and Delivery
  • Quality and Risk Management
  • Systems Thinking
  • Technical/Functional Expertise

PHYSICAL DEMANDS
  • This is a standard desk role requiring extended sitting and computer work

WORK ENVIRONMENT
  • Remote

Here at Allied, we believe that great talent can thrive from anywhere. Our remote friendly culture offers flexibility and the comfort of working from home, while also ensuring you are set up for success. To support a smooth and efficient remote work experience, the internet connection must be obtained through a cable broadband or fiber optic internet service provider with speeds of at least 100Mbps download/25Mbps upload. Reliable internet service is essential for staying connected and productive.
The company has reviewed this job description to ensure that essential functions and basic duties have been included. It is not intended to be construed as an exhaustive list of all functions, responsibilities, skills, and abilities. Additional functions and requirements may be assigned by supervisors as deemed appropriate.
Compensation is not limited to base salary. Allied values our Total Rewards, and offers a competitive Benefit Package including, but not limited to, Medical, Dental, Vision, Life and Disability Insurance, Generous Paid Time Off, Tuition Reimbursement, EAP, and a Technology Stipend.
Allied reserves the right to amend, change, alter, and revise, pay ranges and benefits offerings at any time. All applicants acknowledge that by applying to the position you understand that the specific pay range is contingent upon meeting the qualification and requirements of the role, and for the successful completion of the interview selection and process. It is at the Company's discretion to determine what pay is provided to a candidate within the range associated with the role.

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