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Machine Learning Assistant Jobs in Villa Rica, GA

AppFolio

Sr. Machine Learning Engineer

Atlanta, GA

$100K - $138K/yr

... Assistant (copilot), Flows (AI Agentic workflows) and Performers (autonomous AI Agents). Realm-X ... Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next ...

Schweid & Sons

Machine Operator Apprentice

Atlanta, GA · On-site

$17 - $22/hr

Perform routine inspections to ensure machinery is in good working order, assist in troubleshooting malfunctions, and perform basic repairs as needed. * Observation and Learning: Observe experienced ...

Westrock

Machine Helper

Kennesaw, GA · On-site

$19.66/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... and assistant operator with setups and jam-ups, ensuring that the area surrounding the machine is kept clean of debris and spills What you need to succeed: * A learning mindset * Ability to read ...

AMC Health

Senior Software Engineer Applied AI

Atlanta, GA · On-site

$117K - $155K/yr

... plus the machine learning and LLM pipelines around them. This is one seat that spans four ... Fluency with AI coding assistants (our workflows assume them, with human accountability for every ...

New

Smurfit Westrock

Machine Helper

Kennesaw, GA · On-site

$19.66/hr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

... and assistant operator with setups and jam-ups, ensuring that the area surrounding the machine is kept clean of debris and spills What you need to succeed: * A learning mindset * Ability to read ...

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Showing results 21-40

All JobsMachine Learning JobsMachine Learning Assistant JobsMachine Learning Assistant Jobs in Villa Rica, GA

Machine Learning Assistant information

See Villa Rica, GA salary details

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How much do machine learning assistant jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for machine learning assistant in Villa Rica, GA is $15.76, according to ZipRecruiter salary data. Most workers in this role earn between $14.28 and $16.78 per hour, depending on experience, location, and employer.

What is a machine learning assistant?

A Machine Learning Assistant is a professional who supports the development, implementation, and maintenance of machine learning models and systems. They assist data scientists and engineers by preparing datasets, conducting preliminary data analysis, running experiments, and helping to optimize algorithms. This role often involves coding, testing models, and ensuring the quality and reliability of machine learning solutions. Machine Learning Assistants play a key role in streamlining workflows and enabling faster progress in AI projects.

What are the key skills and qualifications needed to thrive as a machine learning assistant?

To thrive as a Machine Learning Assistant, a solid background in mathematics, statistics, programming (often Python), and foundational knowledge of machine learning algorithms is essential, typically supported by a relevant degree or coursework. Familiarity with tools like TensorFlow, scikit-learn, Jupyter Notebooks, and version control systems such as Git is commonly required. Strong problem-solving abilities, attention to detail, and the capability to communicate findings effectively are standout soft skills in this role. These skills ensure accurate data analysis, effective model building, and successful collaboration within multidisciplinary teams.

What are some common challenges a machine learning assistant may face when supporting data preparation and model training?

Machine Learning Assistants often encounter challenges such as cleaning large, unstructured datasets, identifying and handling missing or inconsistent data, and ensuring data privacy compliance. They also need to communicate effectively with data scientists and engineers to understand project requirements and adapt to evolving priorities. Staying organized and managing multiple tasks simultaneously—such as data preprocessing, feature engineering, and running model experiments—is crucial for success in this role.

What cities near Villa Rica, GA are hiring for Machine Learning Assistant jobs?

Cities near Villa Rica, GA with the most Machine Learning Assistant job openings:

Machine Learning Assistant jobs near you
Infographic showing various Machine Learning Assistant job openings in Villa Rica, GA as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $32,776 per year, or $15.8 per hour.

Machine Learning Engineer

Five and Fly, LLC.

Atlanta, GA

Full-time

Re-posted 28 days ago

Job description

We are seeking a skilled and forward-looking ML Engineer with experience in Large Language Models (LLMs), generative AI, and agentic architectures to join our growing R&D and Applied AI team. This role is critical in helping Oversight deliver the next generation of agentic AI systems for enterprise spend management and risk controls.
 
The ideal candidate has a strong foundation in machine learning, modern deep learning frameworks, and data pipelines, coupled with hands-on experience experimenting with LLMs, small language models (SLMs), multi-agent frameworks, and retrieval-augmented generation (RAG).

You will work closely with AI/ML researchers, data engineers, and product teams to design, implement, and optimize models that power autonomous exception resolution, anomaly detection, and explainable insights. This is a hands-on engineering role where you will not only build and scale ML systems but also actively contribute to cutting-edge applied research in agentic AI.
Core ML/LLM Engineering
  • Contribute to the design, training, fine-tuning, and deployment of ML/LLM models for production.
  • Implement RAG pipelines using vector databases.
  • Work with frameworks like LangChain, LangGraph, MCP to prototype and optimize multi-agent workflows.
  • Develop prompt engineering, optimization, and safety techniques for agentic LLM interactions.
  • Integrate memory, evidence packs, and explainability modules into agentic pipelines.
  • Work hands-on with multiple LLM ecosystems:
    • OpenAI GPT models (GPT-4, GPT-4o, fine-tuned GPTs).
    • Anthropic Claude (Claude 2/3 for reasoning and safety-aligned workflows).
    • Google Gemini (multimodal reasoning, advanced RAG integration).
    • Meta LLaMA (fine-tuned/custom models for domain-specific tasks).
Data & Infrastructure
  • Collaborate with Data Engineering to build and maintain real-time and batch data pipelines that serve ML/LLM workloads.
  • Conduct feature engineering, preprocessing, and embeddings generation for structured and unstructured data.
  • Implement model monitoring, drift detection, and retraining pipelines.
  • Leverage cloud ML platforms (AWS Sagemaker, Databricks ML) for experimentation and scaling.
Research & Applied Innovation
  • Explore and evaluate emerging LLM/SLM architectures and agent orchestration patterns.
  • Experiment with generative AI and multimodal models to extend capabilities beyond text (images, structured financial data).
  • Collaborate with R&D to prototype autonomous resolution agents, anomaly detection models, and reasoning engines.
  • Translate research prototypes into production-ready components.
Collaboration & Delivery
  • Work cross-functionally with R&D, Data Science, Product, and Engineering to deliver business-aligned AI features.
  • Participate in design reviews, architecture discussions, and model evaluations.
  • Document processes, experiments, and results effectively for knowledge sharing.
  • Mentor junior engineers and contribute to ML engineering best practices.
Required
  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field.
  • 3+ years of experience building and deploying ML systems.
  • Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers.
  • Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference optimization).
  • Demonstrated experience with at least two of the following ecosystems:
    1. OpenAI GPT models (chat, assistants, fine-tuning).
    2. Anthropic Claude (safety-first AI for reasoning and summarization).
    3. Google Gemini (multimodal reasoning, enterprise-scale APIs).
    4. Meta LLaMA (open-source, fine-tuned models).
  • Familiarity with vector databases, embeddings, and RAG pipelines.
  • Ability to work with structured and unstructured data at scale.
  • Knowledge of SQL and distributed data frameworks (Spark, Ray).
  • Strong understanding of ML lifecycle: data prep, training, evaluation, deployment, monitoring.
Preferred Qualifications
  • Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen).
  • Knowledge of AI safety, guardrails, and explainability techniques.
  • Hands-on experience deploying ML/LLM solutions in cloud environments (AWS, GCP, Azure).
  • Experience with CI/CD for ML (MLOps), monitoring, and observability.
  • Familiarity with anomaly detection, fraud/risk modeling, or behavioral analytics.
  • Contributions to open-source AI/ML projects or publications in applied ML research.
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