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Remote Plastics Engineer Jobs in Dallas, GA (NOW HIRING)

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

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 ...

CRH

Inside Sales Representative

Atlanta, GA · Remote

$33 - $38/hr

We're a trusted and strategic partner to engineers, contractors, distributors, specifiers ... Job Location This is a remote position- can be based anywhere in the US. Job Responsibilities

Aimpoint Digital

Senior AI Engineer 2026 - US

Atlanta, GA · On-site +1

$100K - $138K/yr

About the Role As a Senior AI Engineer, you will work directly with clients to design, build ... remote work within the US. Atlanta-based applicants will have the opportunity to work in our ...

Aimpoint Digital

Senior AI Engineer 2026 - US

Atlanta, GA · On-site +1

$100K - $138K/yr

About the Role As a Senior AI Engineer, you will work directly with clients to design, build ... remote work within the US. Atlanta-based applicants will have the opportunity to work in our ...

Docebo

Senior Cloud Engineer I

Atlanta, GA · On-site +1

$104K - $138K/yr

The Adventure Ahead As a Senior Cloud Engineer I, you are the backbone of the infrastructure that powers Docebo's global learning platform! You will architect, scale, and secure our AWS-based ...

UnitedHealth Group

Senior DevSecOps Engineer

Atlanta, GA · Remote

$91K - $163K/yr

As a Senior DevSecOps Engineer (Sr DevOps Engineer) within our technology organization, you will be at the forefront of securing, automating, and optimizing our enterprise release pipelines and ...

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All JobsPlastics Engineer JobsRemote Plastics Engineer JobsRemote Plastics Engineer Jobs in Dallas, GA

Remote Plastics Engineer information

See Dallas, GA salary details

$33K

$59K

$98K

How much do remote plastics engineer jobs pay per year?

As of Aug 23, 2026, the average yearly pay for remote plastics engineer in Dallas, GA is $58,963.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,800.00 and $71,800.00 per year, depending on experience, location, and employer.

What is a remote plastics engineer?

A Remote Plastics Engineer designs, develops, and optimizes plastic products, materials, and manufacturing processes while working off-site. They collaborate with teams using digital tools to conduct simulations, material testing, and process improvements. Common responsibilities include CAD modeling, material selection, and ensuring product quality. This role often requires experience in injection molding, extrusion, or other plastics manufacturing techniques. Remote Plastics Engineers communicate with suppliers and manufacturers to ensure efficient production while minimizing costs and environmental impact.

What are the key skills and qualifications needed to thrive as a remote plastics engineer?

To thrive as a Remote Plastics Engineer, you need a solid background in polymer science, plastics manufacturing processes, and product design, typically supported by a degree in chemical, mechanical, or plastics engineering. Familiarity with CAD software (such as SolidWorks or AutoCAD), simulation tools, and knowledge of quality standards like ISO or Six Sigma are often required. Excellent problem-solving, self-motivation, and strong communication skills are vital for effective collaboration in a remote setting. These skills ensure high-quality engineering outputs, effective teamwork, and successful project management from a distance.

What are some common challenges faced by remote plastics engineers and how can they be addressed?

Remote Plastics Engineers often face challenges related to collaborating with manufacturing teams, troubleshooting production issues without being on-site, and staying updated on plant operations. To address these challenges, clear and regular communication through video calls, shared digital documentation, and proactive follow-ups are essential. Using remote monitoring and virtual collaboration tools can help bridge the physical gap with on-site teams. Building strong relationships with colleagues and staying organized are also key strategies for overcoming the unique obstacles of remote engineering work.

What are popular job titles related to Remote Plastics Engineer jobs in Dallas, GA?

For Remote Plastics Engineer jobs in Dallas, GA, the most frequently searched job titles are:

What job categories do people searching Remote Plastics Engineer jobs in Dallas, GA look for?

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What cities near Dallas, GA are hiring for Remote Plastics Engineer jobs?

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Remote Plastics Engineer jobs near you
Infographic showing various Remote Plastics Engineer job openings in Dallas, GA as of August 2026, with employment types broken down into 92% Full Time, 2% Part Time, and 6% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $58,963 per year, or $28.3 per hour.

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Re-posted yesterday

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.