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Remote Image Processing Jobs in Illinois (NOW HIRING)

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 ... whole slide image (WSI) processing Experience with LoRAs, transformer architecture and ...

Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$107K - $147K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... whole slide image (WSI) processing Experience with LoRAs, transformer architecture and ...

Loadsmart

Senior Embedded Systems Engineer

Chicago, IL · On-site +1

United States (Remote) WHAT YOU GET TO DO: * Maintain end-to-end system integrity across the ... Video and Image Encoding Fundamentals: Understanding of modern video codecs such as H.265/HEVC and ...

Quora

AI Automation Engineer -Remote

Edwardsville, IL · On-site +1

$202K - $234K/yr

... GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to ... Use AI as much as possible to automate your own process of creating this software * Collaborate ...

Quora

AI Automation Engineer -Remote

Joliet, IL · On-site +1

$202K - $234K/yr

... GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to ... Use AI as much as possible to automate your own process of creating this software * Collaborate ...

Quora

AI Automation Engineer -Remote

Chicago, IL · On-site +1

$202K - $234K/yr

... GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to ... Use AI as much as possible to automate your own process of creating this software * Collaborate ...

Quora

AI Automation Engineer -Remote

Rockford, IL · On-site +1

$202K - $234K/yr

... GPT Image 1 and more. As AI capabilities rapidly advance, Poe provides a single platform to ... Use AI as much as possible to automate your own process of creating this software * Collaborate ...

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Remote Image Processing information

What is remote image processing?

Remote image processing refers to analyzing and manipulating digital images from a distance, typically using cloud-based or networked systems. Professionals in this field use specialized software and algorithms to enhance, interpret, or extract information from images without being physically present at the image acquisition site. This is commonly used in fields like satellite imaging, medical diagnostics, and security surveillance. Working remotely allows image processing experts to collaborate globally and access large datasets stored on remote servers.

What is the difference between Remote Image Processing vs Remote Data Entry?

AspectRemote Image ProcessingRemote Data Entry
Required SkillsImage editing, software proficiency, attention to detailTyping speed, accuracy, basic computer skills
Work EnvironmentDesign software, image platforms, cloud toolsSpreadsheets, databases, online forms
Industry UsagePhotography, media, e-commerceAdministration, research, healthcare

Remote Image Processing involves editing and managing visual content, requiring skills in image software and attention to detail. Remote Data Entry focuses on inputting information accurately into digital systems, emphasizing typing skills and data accuracy. Both roles are performed remotely, often within similar industries, but serve different functions—visual content management versus information management.

What are the key skills and qualifications needed to thrive as a Remote Image Processing Specialist, and why are they important?

To thrive as a Remote Image Processing Specialist, you need a strong background in computer vision, image analysis, and programming (often with degrees in computer science, electrical engineering, or related fields). Familiarity with tools like MATLAB, Python libraries (such as OpenCV or scikit-image), and cloud-based image processing platforms is typically required. Attention to detail, problem-solving abilities, and effective remote communication are valuable soft skills in this role. These competencies are crucial for accurately analyzing visual data, automating processes, and collaborating efficiently across distributed teams.

What are the main collaboration tools and practices used by remote image processing teams?

Remote image processing teams typically rely on a combination of cloud-based storage solutions, communication platforms like Slack or Microsoft Teams, and collaborative coding environments such as GitHub or GitLab. These tools enable seamless sharing of large datasets, version control of processing scripts, and real-time feedback on project progress. Regular virtual meetings and clear documentation are also essential to ensure alignment and productivity across distributed team members. Familiarity with these collaboration practices can help new hires integrate smoothly and contribute effectively from day one.
What are the most commonly searched types of Image Processing jobs in Illinois? The most popular types of Image Processing jobs in Illinois are:
What are popular job titles related to Remote Image Processing jobs in Illinois? For Remote Image Processing jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Remote Image Processing jobs in Illinois look for? The top searched job categories for Remote Image Processing jobs in Illinois are:
What cities in Illinois are hiring for Remote Image Processing jobs? Cities in Illinois with the most Remote Image Processing job openings:
Remote Image Processing jobs near you

Senior Machine Learning Engineer

Career Renew

Chicago, IL • Remote

$165K - $225K/yr

Full-time

Posted 13 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.