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Entry Level Remote Electrical Engineering Jobs in Georgia

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 ... Electrical Engineering, or a related field Deep expertise in computer vision and deep learning ...

KEYENCE

Field Application Engineer '27

Atlanta, GA · On-site +1

$53K - $80K/yr

Locations | Entry-Level | Full-Time Are you ready to launch your career with one of the world ... Provide on-call, on-site and remote technical support, training, and troubleshooting * Travel ...

TEKsystems

Programmer Analyst

Atlanta, GA · Remote

$30 - $35/hr

Experience Level Entry Level Job Type & Location This is a Contract to Hire position based out of ... remote position. Application Deadline This position is anticipated to close on Aug 18, 2026. About ...

Johnson Controls

High Level Engineer - Controls

Atlanta, GA · On-site +1

$80K - $103K/yr

This role will provide Pre-sales engineering, design and estimation during project design or ... This position is REMOTE and can be located anywhere within the US. How you will do it Under general ...

Becton, Dickinson and Company

$14.50 - $19.25/hr

It takes the imagination and passion of all of us-from design and engineering to the manufacturing ... S.A. remote. Role Summary The Associate Service Sales Representative is an entrylevel sales role ...

Heritage Werks, Inc.

Project Management Analyst

Duluth, GA · On-site +1

$107K/yr

Remote or Hybrid (Duluth, GA) Requirements What You'll Be Responsible For Project Management ... Internship or entry-level project management experience will be considered. Preferred Experience ...

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Entry Level Remote Electrical Engineering information

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

To thrive as an Entry Level Remote Electrical Engineer, you need a solid understanding of electrical engineering principles, a relevant bachelor's degree, and basic experience with circuit design and analysis. Familiarity with CAD software (like AutoCAD or Altium), simulation tools (such as MATLAB or LTspice), and remote collaboration platforms is typically required. Strong problem-solving abilities, clear written communication, and self-motivation are essential soft skills for working independently and with distributed teams. These skills and tools are crucial for delivering quality engineering solutions efficiently and effectively in a remote work environment.

What is an entry level remote electrical engineering job?

An entry level remote electrical engineering job is a position for recent graduates or those new to the field, where engineers work from a remote location—such as their home—rather than a traditional office or lab. These roles typically involve tasks like assisting with circuit design, CAD drafting, testing, documentation, and collaborating with teams online. Entry level remote electrical engineers may support senior engineers on projects in industries such as energy, telecommunications, electronics, or manufacturing. They use digital tools and video conferencing to communicate and contribute to engineering projects. This setup allows flexibility but also requires good self-management and communication skills.

How does an entry level remote electrical engineer typically collaborate with team members and senior engineers?

As an entry-level remote electrical engineer, you will frequently use digital collaboration tools such as video conferencing, project management software, and cloud-based design platforms to interact with your team. Regular check-in meetings, virtual code/design reviews, and shared project documentation help ensure alignment and continuous feedback from senior engineers. It's important to be proactive in communication and ask questions, as remote settings often require more initiative to stay connected and supported. While you may work independently on certain tasks, you'll often collaborate on larger projects, troubleshooting, and documentation to contribute effectively to team goals.

What is the difference between Entry Level Remote Electrical Engineering vs Entry Level Remote Electronics Technician?

AspectEntry Level Remote Electrical EngineeringEntry Level Remote Electronics Technician
Required CredentialsBachelor's degree in electrical engineering or related fieldAssociate's degree or technical certification in electronics
Work EnvironmentDesign, testing, and development in remote or office settingsInstallation, maintenance, and troubleshooting remotely or on-site
Industry UsagePower, telecommunications, consumer electronicsManufacturing, repair services, consumer electronics
Common Search/ComparisonDesign and development rolesTechnical support and maintenance roles

Entry Level Remote Electrical Engineering typically involves designing and testing electrical systems with a focus on development, requiring a bachelor's degree. In contrast, Entry Level Remote Electronics Technician emphasizes troubleshooting and maintenance, often requiring technical certifications. Both roles can be performed remotely and are essential in their respective industries, but they differ in responsibilities and required credentials.

What are the most commonly searched types of Remote Electrical Engineering jobs in Georgia?

The most popular types of Remote Electrical Engineering jobs in Georgia are:

Entry Level Remote Electrical Engineering jobs near you
Infographic showing various Entry Level Remote Electrical Engineering job openings in Georgia as of August 2026, with employment types broken down into 96% Full Time, and 4% Part Time. Highlights an 100% Remote job distribution.

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Re-posted 23 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.