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Remote Google Cloud Machine Learning Engineer Jobs in Illinois

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

... Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary ... cloud ML infrastructure (AWS, GCP, or Azure) Knowledge of handling large scale image data, data ...

Autodesk

Senior Machine Learning Test Engineer

Ohio, IL · On-site +1

$104K - $135K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East ... Experience with cloud providers (e.g., AWS, Azure, Google Cloud Platform) * Experience testing ML ...

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Quora

$139K - $168K/yr

Our team of Machine Learning Engineers have high impact by advancing the current Machine Learning ... LI-SS2 LI-REMOTE

Burwood Group, Inc

Sr. Consultant, Cloud Solutions

Chicago, IL · On-site +1

$60.25 - $82.25/hr

Active Google Cloud Professional Certifications (e.g., Cloud Architect, Cloud DevOps Engineer, Machine Learning Engineer) are highly preferred. CNCF (CKA/CKAD) or HashiCorp certifications are a ...

Adidev Technologies

AI/ML

Des Plaines, IL · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... Azure, Google Cloud and OpenAI. * Software engineering and/or Data Engineering background ...

Adidev Technologies Inc

AI/ML

Chicago, IL · Remote

Adidev is looking for an adept Machine Learning Engineer to take the helm in deploying advanced ... such as AWS, Databricks, Azure, Google Cloud and OpenAI. Software engineering and/or Data ...

NinjaTrader

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 ...

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All JobsGoogle Cloud Machine Learning Engineer JobsRemote Google Cloud Machine Learning Engineer JobsRemote Google Cloud Machine Learning Engineer Jobs in Illinois

Remote Google Cloud Machine Learning Engineer information

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 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:
Remote Google Cloud Machine Learning Engineer jobs near you
Infographic showing various Remote Google Cloud Machine Learning Engineer job openings in Illinois as of July 2026, with employment types broken down into 88% Full Time, 7% Part Time, and 5% Contract. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Senior Machine Learning Engineer

Career Renew

Chicago, IL • Remote

$165K - $225K/yr

Full-time

Posted 6 days ago

Job description

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 equity.
We are the leading virtual staining company revolutionizing digital pathology adoption worldwide through cutting-edge AI-powered technology. Our solutions deliver diagnostic-quality results in minutes while preserving tissue samples for comprehensive analysis.
Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual staining from a single tissue sample, eliminating the bottlenecks and limitations of traditional chemical staining processes. This innovation supports the critical evolution from research applications to clinical deployment, empowering laboratories to advance their digital pathology capabilities while reducing chemical waste, improving operational efficiency, and expanding diagnostic possibilities.

About the Role

We are seeking an experienced Senior ML Engineer to join our team who owns the representation-learning and generative modeling stack that powers Pictor’s virtual staining. The ideal candidate will have deep expertise in Machine Learning and building generalizable, production-ready models, and evaluations that stand up in clinical workflows.
Design and implement novel computer vision and deep learning algorithms for virtual staining and digital pathology applications
Conduct rigorous experiments to evaluate algorithm performance, validate research hypotheses, and drive iterative improvements
Develop and advance ML models leveraging Vision Transformers, Diffusion Models, GANs, and generative architectures for image-to-image translation tasks
Apply classical and learned image enhancement, denoising, and semantic segmentation techniques to histopathology imaging challenges
Explore image representation in latent space for efficient, high-fidelity virtual staining
Stay current with state-of-the-art research, identifying opportunities to apply novel techniques to PictorLabs’ product roadmap

Collaboration
Collaborate with ML Engineering and software teams to translate research prototypes into production-ready systems meeting latency and throughput requirements
Work with large-scale pathology datasets to train, validate, and fine-tune foundation models and custom architectures
Partner with software engineers, data scientists, and pathology domain experts to integrate research into production systems
Contribute to best practices for data engineering, data governance, and data quality across research and production pipelines
Leverage AI coding and ideation tools to accelerate research velocity and prototype new approaches

Required Qualifications

PhD (preferred) or Master’s degree in Computer Science, Electrical Engineering, or a related field
Deep expertise in computer vision and deep learning, with hands-on experience in one or more of: Vision Transformers, Diffusion Models, GANs, semantic segmentation, or classical image enhancement and denoising
Expert proficiency in Python and PyTorch and other scientific computing environments a plus
Strong mathematical foundation in linear algebra, probability, and optimization
Experience with large-scale model training, distributed computing, or cloud ML infrastructure (AWS, GCP, or Azure)
Knowledge of handling large scale image data, data version controls, model registry, has experience dealing with ML lifecycles
Experience with feature search, data balancing, and data curation pipelines.
Knowledge of software engineering best practices including version control (Git) and CI/CD pipelines
Excellent collaboration and communication skills, with the ability to work effectively in a fast-paced, cross-functional international startup environment
Extensive use of AI tools for coding, optimization, and ideation

Preferred Qualifications

Experience with medical imaging, digital pathology, or whole slide image (WSI) processing
Experience with LoRAs, transformer architecture and state of the art image to image translation models (Flux 2, Z-Image) and the Hugging face ecosystem
Background in generative models and fine-tuning of foundation models
Experience with GPU acceleration and optimization, including CUDA kernel engineering, TensorRT/ONNX export, and inference serving frameworks such as Triton
Experience with hosting computer vision model inference on NVIDIA DGX Spark.
Understanding of FDA regulatory requirements for AI/ML in medical devices
Experience with MLOps tools (MLflow, Kubeflow) and model versioning practices
Develop tools and frameworks to streamline ML research workflows, experimentation, and reproducibility

What We Offer

The opportunity to work on technology that directly improves patient outcomes and transforms clinical diagnostics, alongside a talented team of engineers and researchers pushing the boundaries of AI in healthcare. You will have the freedom to pursue high-impact research while seeing your work deployed at scale in real clinical environments.