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Entry Level Remote Medical Coder Jobs in Sharpsburg, GA

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 ... coding, optimization, and ideation Preferred Qualifications Experience with medical imaging ...

Capgemini

Aerospace Software Engineer

Atlanta, GA · On-site +1

$82K/yr

Conduct code reviews, builds, and configuration management * Support flight test integration ... Medical, dental, and vision coverage (or provincial healthcare coordination in Canada) * Retirement ...

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Entry Level Remote Medical Coder information

See Sharpsburg, GA salary details

$14

$20

$31

How much do entry level remote medical coder jobs pay per hour?

As of Aug 21, 2026, the average hourly pay for entry level remote medical coder in Sharpsburg, GA is $20.72, according to ZipRecruiter salary data. Most workers in this role earn between $16.68 and $22.21 per hour, depending on experience, location, and employer.

What is an entry level remote medical coder?

Entry level remote medical coders are professionals who assign standardized codes to medical diagnoses, procedures, and services using patient records, typically working from home. They help ensure that healthcare providers and facilities receive proper reimbursement from insurance companies by accurately coding medical information. Entry level positions are typically for those new to the field, often requiring a coding certification and strong attention to detail. Remote coders use specialized software and must adhere to healthcare privacy regulations. This role offers flexibility and the opportunity to start a career in healthcare administration.

What does an entry level remote medical coder do?

An entry-level remote medical coder works from home to handle data entry related to medical records and healthcare insurance claims. As a remote medical coder, your duties include listening to and transcribing doctors’ notes, cross-referencing medical codes and reimbursement and billing information, and querying clinics or healthcare professionals when information does not match up with your records. Responsibilities also include noting all patient treatment options, determining whether or not they have the proper health care coverage, and keeping meticulous records.

What are the key skills and qualifications needed to thrive as an entry level remote medical coder?

To thrive as an Entry Level Remote Medical Coder, you need a foundational understanding of medical terminology, anatomy, and coding systems (such as ICD-10, CPT, and HCPCS), typically supported by a relevant certification like CPC or CCA. Familiarity with electronic health records (EHR) systems and medical coding software is essential for accurate data entry and code assignment. Attention to detail, self-motivation, and strong organizational skills are vital soft skills for maintaining accuracy and productivity in a remote setting. These skills are crucial to ensure precise coding, compliance with regulations, and efficient remote workflow.

What are some common challenges faced by entry level remote medical coders, and how can these be managed?

Entry level remote medical coders often face challenges such as learning to interpret complex medical records, staying updated with coding guidelines, and managing productivity without onsite supervision. To manage these, it's important to establish a structured daily routine, utilize company-provided resources and training, and proactively communicate with supervisors or team members when questions arise. Building a support network with other remote coders and participating in online forums can also help address uncertainties and foster professional growth.

What is the difference between Entry Level Remote Medical Coder vs Medical Biller?

AspectEntry Level Remote Medical CoderMedical Biller
CertificationsCertified Coding Associate (CCA), CPCCertified Professional Biller (CPB), CPC
Work EnvironmentRemote, healthcare facilities, coding companiesRemote, healthcare providers, billing companies
Primary ResponsibilitiesAssigning medical codes to diagnoses and proceduresSubmitting and managing insurance claims, billing patients

While both roles work closely within healthcare revenue cycle management, Entry Level Remote Medical Coders focus on accurately coding medical records, whereas Medical Billers handle insurance claims and payments. Understanding these differences helps job seekers identify the right career path in healthcare administration.

Can you get an entry level remote medical coder job with no experience?

Entry level remote medical coder positions often do not require prior experience, but candidates typically need a certification such as CPC or CCS and basic knowledge of medical coding guidelines. Employers may provide on-the-job training, making it possible for newcomers to start without previous coding experience.
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Entry Level Remote Medical Coder jobs near you
Infographic showing various Entry Level Remote Medical Coder job openings in Sharpsburg, GA as of August 2026, with employment types broken down into 95% Full Time, and 5% Temporary. Highlights an 100% Remote job distribution, with an average salary of $43,106 per year, or $20.7 per hour.

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Re-posted 29 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.