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Remote Nvidia Machine Learning Jobs in Chicago, IL

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... NVIDIA DGX Spark. Understanding of FDA regulatory requirements for AI/ML in medical devices ...

Addison Group

Sr. Data Scientist

Chicago, IL · On-site +1

$85 - $100/hr

Remote Contract Pay: $85/hr - $100/hr The Senior Data Scientist will design and implement AI, Machine Learning, and Operations Research models that transform business objectives into data-driven ...

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All JobsRemote Nvidia Machine Learning JobsRemote Nvidia Machine Learning Jobs in Chicago, IL

Remote Nvidia Machine Learning information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

How much do remote nvidia machine learning jobs pay per year?

As of Jun 15, 2026, the average yearly pay for remote nvidia machine learning in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

Can you work for NVIDIA remotely?

Remote Nvidia machine learning roles are available, with many positions allowing employees to work from home depending on the team and project requirements. Candidates typically need strong technical skills in machine learning, experience with Nvidia tools like CUDA, and may require specific certifications or hardware setup for remote work. Availability varies by role and location policies.

Which 5 jobs will survive AI?

Remote Nvidia Machine Learning roles are likely to persist as they require specialized skills in AI, deep learning, and GPU programming. Jobs involving complex problem-solving, creativity, and human interaction, such as data scientists, AI researchers, software engineers, cybersecurity specialists, and technical trainers, are expected to remain in demand despite AI advancements.

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

Is it difficult to get hired at NVIDIA?

Getting hired for a remote Nvidia machine learning role can be competitive due to the company's high standards and specialized skill requirements. Candidates typically need strong expertise in machine learning, deep learning frameworks, and relevant programming languages, along with a solid educational background. Demonstrating experience with Nvidia technologies and certifications can improve chances of selection.

What is the difference between Remote Nvidia Machine Learning vs Remote Data Scientist?

AspectRemote Nvidia Machine LearningRemote Data Scientist
Required CredentialsDeep learning, GPU programming, Nvidia certificationsStatistics, programming, data analysis
Work EnvironmentFocus on GPU-accelerated ML models, Nvidia toolsData analysis, modeling, visualization
Industry UsageAI, autonomous vehicles, gaming, HPCBusiness analytics, research, finance

Remote Nvidia Machine Learning specialists focus on developing GPU-accelerated AI models using Nvidia technologies, often requiring specific certifications and expertise in GPU programming. In contrast, Remote Data Scientists analyze data, build predictive models, and interpret results across various industries. While both roles involve data and programming skills, Nvidia Machine Learning roles are more specialized in GPU-based AI development, whereas Data Scientists have broader data analysis responsibilities.

What are the most commonly searched types of Nvidia Machine Learning jobs in Chicago, IL? The most popular types of Nvidia Machine Learning jobs in Chicago, IL are:
Remote Nvidia Machine Learning jobs near you

Senior Machine Learning Engineer

Career Renew

Chicago, IL • Remote

$165K - $225K/yr

Full-time

Posted 22 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.