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Remote Image Analysis Jobs in Georgia (NOW HIRING)

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

... remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ... analysis. Our breakthrough DeepStain™ and ReStain™ technologies enable unlimited virtual ...

Cox Communications, Inc.

Product Manager II

Atlanta, GA · On-site +1

$89.40K - $134K/yr

... photographers, remote condition reviewers, buyer decision-makers). * Partner with imaging ... based on analysis of inspection data, image quality metrics, and field feedback. * Support ...

Crawford and Company

Multi-Line Adj

Peachtree Corners, GA · On-site +1

$60K - $70K/yr

Now Hiring | Multi-Line Adjuster (Remote) We're seeking an experienced Multi-Line Adjuster with 3-5 ... Uphold and project the corporate image by participating in industry organizations and functions.

Manulife

$94.60K - $111.80K/yr

This is a remote role open to any location in continental US Manulife is a leading international ... The incumbent will analyze decisions without compromising overall underwriting policies and should ...

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Remote Image Analysis information

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

To thrive as a Remote Image Analyst, you need a solid background in image processing, pattern recognition, and a relevant degree in fields like computer science or engineering. Familiarity with software such as MATLAB, Python (with libraries like OpenCV), and GIS platforms is typically required, along with certifications in data analysis or remote sensing. Attention to detail, analytical thinking, and effective communication are essential soft skills for interpreting images and sharing findings with stakeholders. These skills ensure accurate data interpretation, support decision-making, and enable seamless collaboration in remote work environments.

What are some common challenges faced in a remote image analysis role, and how can they be addressed?

One common challenge in remote image analysis is maintaining effective communication with team members and project stakeholders, as collaboration often relies on digital platforms. Additionally, handling large datasets and ensuring secure data transfer can be technically demanding in a remote setup. To address these issues, professionals should become proficient with collaborative tools (such as Slack, Zoom, or project management software) and follow best practices for data security and version control. Regular check-ins and clear documentation also help ensure smooth workflow and minimize misunderstandings.

What is remote image analysis?

Remote image analysis is the process of examining and interpreting images from a distance, often using specialized software and cloud-based platforms. Professionals in this field analyze images from sources such as satellites, drones, medical imaging devices, or security cameras to extract useful information without being physically present. This approach allows for efficient data processing, real-time collaboration, and accessibility from anywhere with an internet connection. Remote image analysis is commonly used in industries like healthcare, agriculture, environmental monitoring, and security.

What is the difference between Remote Image Analysis vs Remote Data Annotation?

AspectRemote Image AnalysisRemote Data Annotation
Primary FocusInterpreting and analyzing images to extract meaningful informationLabeling and tagging data to prepare datasets for machine learning
Required SkillsImage recognition, pattern analysis, attention to detailData labeling, understanding of annotation tools, accuracy
Work EnvironmentRemote, often flexible hours, tech-focusedRemote, collaborative platforms, tech and communication skills
Industry UsageHealthcare, security, autonomous vehiclesAI, machine learning, computer vision projects

Remote Image Analysis involves interpreting images to extract insights, often requiring specialized visual skills. Remote Data Annotation focuses on labeling data to train AI models, emphasizing accuracy and consistency. Both roles are remote, industry-specific, and essential for AI development, but they differ in their core tasks and skill sets.

What are the most commonly searched types of Image Analysis jobs in Georgia? The most popular types of Image Analysis jobs in Georgia are:
What are popular job titles related to Remote Image Analysis jobs in Georgia? For Remote Image Analysis jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Remote Image Analysis jobs in Georgia look for? The top searched job categories for Remote Image Analysis jobs in Georgia are:
What cities in Georgia are hiring for Remote Image Analysis jobs? Cities in Georgia with the most Remote Image Analysis job openings:
Remote Image Analysis jobs near you
Infographic showing various Remote Image Analysis job openings in Georgia as of May 2026, with employment types broken down into 81% Full Time, 13% Part Time, and 6% Contract. Highlights an 56% In-person, 13% Hybrid, and 31% Remote job distribution.

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • 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.