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Remote Monitoring Evaluation Learning Jobs in Decatur, 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 ... evaluations that stand up in clinical workflows. Design and implement novel computer vision and ...

ICF

Senior Transmission Line Engineer - REMOTE

Atlanta, GA · Remote

$100K - $138K/yr

Committed to continuous learning and process improvement, consistently seeking opportunities to ... Perform key engineering studies such as conductor economic evaluations, lightning performance ...

Xplor

Risk Analyst- REMOTE

Atlanta, GA · Remote

Analyst is responsible for evaluating patterns in merchant processing activity and researching ... Monitor emerging trends and threats in the payments industry, adapting risk assessment ...

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All JobsRemote Monitoring Evaluation Learning JobsRemote Monitoring Evaluation Learning Jobs in Decatur, GA

Remote Monitoring Evaluation Learning information

See Decatur, GA salary details

$31.7K

$62.3K

$97.1K

How much do remote monitoring evaluation learning jobs pay per year?

As of Jun 21, 2026, the average yearly pay for remote monitoring evaluation learning in Decatur, GA is $62,271.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,900.00 and $73,200.00 per year, depending on experience, location, and employer.

What is the difference between Remote Monitoring Evaluation Learning vs Remote Data Analyst?

AspectRemote Monitoring Evaluation LearningRemote Data Analyst
Primary FocusMonitoring, evaluating, and learning from programs or projects to improve outcomesAnalyzing data sets to identify trends, generate reports, and support decision-making
Required SkillsMonitoring tools, evaluation methodologies, learning frameworks, data collectionStatistical analysis, data visualization, database management, programming skills
Work EnvironmentFieldwork, program sites, remote collaboration with teamsOffice or remote, primarily computer-based work
Common CertificationsMonitoring and Evaluation (M&E) certifications, learning frameworksData analysis certifications, statistical software training

Remote Monitoring Evaluation Learning professionals focus on assessing program performance and fostering continuous improvement through evaluation and learning. In contrast, Remote Data Analysts primarily analyze data to support strategic decisions. While both roles require data skills, M&E emphasizes evaluation methodologies and learning frameworks, whereas Data Analysts focus on statistical analysis and data management.

What are the typical challenges faced when working in a remote Monitoring, Evaluation, and Learning (MEL) role, and how can they be addressed?

Professionals in remote MEL roles often encounter challenges such as coordinating across time zones, ensuring effective communication with project teams, and accessing reliable data from field locations. To address these, it's important to establish regular virtual check-ins, utilize collaborative digital tools, and build strong relationships with local partners who can facilitate data collection and validation. Proactively setting clear expectations and documentation practices also helps maintain the quality and timeliness of MEL deliverables.

What are the key skills and qualifications needed to thrive as a Remote Monitoring, Evaluation, and Learning (MEL) Specialist, and why are they important?

To thrive as a Remote Monitoring, Evaluation, and Learning (MEL) Specialist, you need a solid background in data analysis, project management, and research methodologies, often supported by a degree in social sciences or a related field. Familiarity with statistical software (such as SPSS or Stata), data visualization tools, and digital survey platforms is typically required, along with knowledge of MEL frameworks. Strong communication, problem-solving, and adaptability are essential soft skills to effectively collaborate with remote teams and stakeholders. These skills ensure accurate program assessment, informed decision-making, and continuous improvement of projects, even when working from a distance.

What is Remote Monitoring, Evaluation, and Learning (MEL)?

Remote Monitoring, Evaluation, and Learning (MEL) refers to the practice of overseeing and assessing projects or programs from a distance, often using digital tools and technology. This approach allows organizations to collect data, track progress, and analyze outcomes without being physically present on-site. Remote MEL is especially useful for projects in hard-to-reach or high-risk areas, enabling timely decision-making and adaptive management. It involves methods such as online surveys, mobile data collection, and remote interviews to ensure effective project monitoring and learning.
What job categories do people searching Remote Monitoring Evaluation Learning jobs in Decatur, GA look for? The top searched job categories for Remote Monitoring Evaluation Learning jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Remote Monitoring Evaluation Learning jobs? Cities near Decatur, GA with the most Remote Monitoring Evaluation Learning job openings:
Remote Monitoring Evaluation Learning jobs near you

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Posted 28 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.