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Remote Validation Engineer Jobs in Mableton, GA (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 ... validate research hypotheses, and drive iterative improvements Develop and advance ML models ...

FHR

M6.20 MuleSoft Lead (100% Remote)

Atlanta, GA · Remote

Build and optimize Mule flows, scopes, error handling strategies, message filters, validation ... Utilize CI/CD tools such as Git, Maven, or Azure DevOps for streamlined development. * Leverage ...

EnSafe Inc.

Industrial Wastewater Engineer

Atlanta, GA · On-site +1

$95K - $160K/yr

Valid driver's license to operate a vehicle in the U.S. Why Join EnSafe? * Employee-Owned Advantage ... S.-based remote position will be based upon a variety of factors such as geographic location ...

Tetra Tech

Civil Engineer III

Atlanta, GA · On-site +1

This opportunity is remote and/or hybrid-friendly that can be performed from a wide range of ... A valid driver's license and clean driving record is required for this position * Must be a U.S ...

Tetra Tech

Civil Engineer III

Atlanta, GA · On-site +1

This opportunity is remote and/or hybrid-friendly that can be performed from a wide range of ... A valid driver's license and clean driving record is required for this position * Must be a U.S ...

Harness

AppSec Sales Engineer East

Atlanta, GA · Remote

$56.50 - $75.50/hr

Work Location * Remote work out of ATL What You Will Have At Harness * Competitive salary ... The OTE Range is $220,000 - $290,000 A valid authorization to work in the U.S. is required.

Iterable

Software Engineer II

Atlanta, GA · On-site +1

$93K - $128K/yr

... remote employees worldwide-we are committed to building a diverse and inclusive workplace. We ... Build and refine the systems engineers use to compile, test, package, and validate their changes ...

Hyperproof

Senior DevSecOps Engineer

Atlanta, GA · Remote

$110K - $151K/yr

Senior DevSecOps Engineer (Remote-based role that requires US-citizenship) About us Hyperproof is ... It's an exciting time to be at Hyperproof; we raised our Series B round in 2023, validating our ...

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Remote Validation Engineer information

See Mableton, GA salary details

$20

$47

$71

How much do remote validation engineer jobs pay per hour?

As of Aug 2, 2026, the average hourly pay for remote validation engineer in Mableton, GA is $47.28, according to ZipRecruiter salary data. Most workers in this role earn between $35.87 and $57.50 per hour, depending on experience, location, and employer.

What are the typical day-to-day responsibilities of a Remote Validation Engineer?

Remote Validation Engineers are responsible for developing and executing test plans, analyzing results, and documenting findings to ensure products meet required standards and specifications. They often collaborate virtually with design, development, and quality teams to identify issues and recommend improvements. Daily tasks may include running automated tests, preparing validation reports, participating in team meetings, and troubleshooting system behaviors. Adapting to shifting project requirements and effectively communicating in a remote setting are also integral parts of the role.

What are the key skills and qualifications needed to thrive in the Remote Validation Engineer position, and why are they important?

To thrive as a Remote Validation Engineer, you need a strong background in engineering or computer science, expertise in validation protocols, and experience with testing methodologies. Familiarity with validation tools such as simulation software, automated test platforms, and knowledge of industry compliance standards (e.g., ISO, FDA, or automotive standards) is typically required, and certifications like ISTQB can be beneficial. Excellent problem-solving skills, attention to detail, and strong written and verbal communication are important for collaborating across distributed teams. These skills ensure the effectiveness and reliability of complex products or systems while supporting seamless teamwork in a remote work environment.

What is a Remote Validation Engineer job?

A Remote Validation Engineer is responsible for testing and verifying that products, systems, or software meet required specifications and function correctly. They develop test plans, run simulations, analyze data, and document results—all while working remotely. This role is common in industries like automotive, semiconductor, and software development, ensuring quality and compliance with standards. Strong technical skills, attention to detail, and proficiency with validation tools are essential.

What are popular job titles related to Remote Validation Engineer jobs in Mableton, GA? For Remote Validation Engineer jobs in Mableton, GA, the most frequently searched job titles are:
What cities near Mableton, GA are hiring for Remote Validation Engineer jobs? Cities near Mableton, GA with the most Remote Validation Engineer job openings:
Remote Validation Engineer jobs near you

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Re-posted 11 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.