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Weekend No Experience Machine Learning Jobs in Decatur, GA

Machine Operator Apprentice

Atlanta, GA · On-site

$17 - $22/hr

Observation and Learning: Observe experienced machine operators to gain knowledge and improve skills. * Safety and Cleanliness: Maintain a clean and safe work area, adhering to company and regulatory ...

Develop tools and frameworks to enable scalable development of machine learning models and data ... Bonus: Experience with Databricks / Spark in addition to using multiple Cloud services' data ...

Machine Operator

Hampton, GA · On-site

$16.75 - $19.75/hr

Machine Operator - Bottle Filling Facility 2nd Shift | Monday-Friday, 3:00 PM - 1:00 AM Weekend and overtime as required We are seeking experienced Machine Operators to join a fast-paced bottle ...

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Weekend No Experience Machine Learning information

See Decatur, GA salary details

$11

$17

$28

How much do weekend no experience machine learning jobs pay per hour?

As of May 30, 2026, the average hourly pay for weekend no experience machine learning in Decatur, GA is $17.56, according to ZipRecruiter salary data. Most workers in this role earn between $15.96 and $17.84 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Machine Learning professional with no prior experience working weekends, and why are they important?

To thrive as a Machine Learning professional, foundational knowledge in mathematics, statistics, and programming (especially Python) is essential, typically demonstrated through coursework or self-directed learning. Familiarity with machine learning libraries such as scikit-learn or TensorFlow and version control systems like Git is highly beneficial, even at an entry level. Curiosity, problem-solving abilities, and effective communication help newcomers stand out as they learn quickly and collaborate with more experienced team members. These skills and qualities are crucial to building practical expertise, contributing to projects, and adapting to the evolving demands of machine learning roles.

What kind of support and training can I expect as someone starting a weekend machine learning role with no prior experience?

In a weekend machine learning role designed for beginners, you can typically expect onboarding sessions, access to online learning materials, and mentorship from more experienced team members. Many organizations provide structured guidance through tutorials, code reviews, and collaborative projects to help you build foundational skills. You’ll likely be assigned manageable tasks that allow you to gradually familiarize yourself with real datasets and tools, while regular feedback ensures your steady progress. Team meetings and open communication channels are common, so don’t hesitate to ask questions and seek help as you learn.

What is a Weekend No Experience Machine Learning job?

A Weekend No Experience Machine Learning job is a part-time opportunity typically scheduled on weekends for individuals interested in machine learning but who have little or no prior experience in the field. These jobs are designed for beginners and may involve tasks such as data labeling, assisting with simple coding projects, or supporting research teams. They provide a great entry point for those looking to gain hands-on experience, learn industry tools, and build their resumes while balancing other commitments like school or a full-time job.

What is the difference between Weekend No Experience Machine Learning vs Weekend Data Analyst?

AspectWeekend No Experience Machine LearningWeekend Data Analyst
Required CredentialsBasic understanding of programming, no formal certification neededBasic knowledge of data analysis tools, possibly some certifications
Work EnvironmentProject-based, flexible hours, often remotePart-time, flexible hours, often remote or on-site
Industry UsageTech, finance, healthcare, startupsBusiness, marketing, finance, consulting

Weekend No Experience Machine Learning roles focus on introductory tasks like data preprocessing and basic model training, suitable for beginners. Weekend Data Analyst positions involve analyzing datasets, creating reports, and supporting decision-making. Both roles are flexible and often part-time, but they differ in technical depth and industry focus.

What are popular job titles related to Weekend No Experience Machine Learning jobs in Decatur, GA? For Weekend No Experience Machine Learning jobs in Decatur, GA, the most frequently searched job titles are:
What job categories do people searching Weekend No Experience Machine Learning jobs in Decatur, GA look for? The top searched job categories for Weekend No Experience Machine Learning jobs in Decatur, GA are:
What cities near Decatur, GA are hiring for Weekend No Experience Machine Learning jobs? Cities near Decatur, GA with the most Weekend No Experience Machine Learning job openings:

Senior Machine Learning Engineer

Career Renew

Atlanta, GA • Remote

$165K - $225K/yr

Full-time

Posted 6 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.