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Home Based Python Machine Learning Jobs in Conyers, GA

Speria

Machine Learning Operations Engineer

Atlanta, GA · On-site

$120 - $180/hr

Experience working with cloud-based environments for deploying and operating data or machine learning systems. * Strong programming skills in Python and experience with scripting and automation for ...

Cox Automotive

Machine Learning Lead Engineer

Norcross, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Chamblee, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Dunwoody, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Conley, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Atlanta, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Redan, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

Cox Automotive

Machine Learning Lead Engineer

Decatur, GA · On-site

$134K - $224K/yr

Develops AI/ML-powered solutions based on business needs. Researches, implements, and tests machine learning methods to create product features, automate workflows, extract insights from data, and ...

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Showing results 41-60

All JobsHome Based Python Machine Learning JobsHome Based Python Machine Learning Jobs in Conyers, GA

Home Based Python Machine Learning information

See Conyers, GA salary details

$11

$51

$75

How much do home based python machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for home based python machine learning in Conyers, GA is $51.32, according to ZipRecruiter salary data. Most workers in this role earn between $42.31 and $58.27 per hour, depending on experience, location, and employer.

What is the difference between Home Based Python Machine Learning vs Data Analyst?

AspectHome Based Python Machine LearningData Analyst
Required CredentialsPython programming, machine learning certifications, data analysis skillsData analysis certifications, SQL, Excel, Python or R knowledge
Work EnvironmentRemote, home-based, often project-focusedRemote or on-site, business or client-focused
Industry UsageTech, finance, healthcare, e-commerceBusiness, marketing, finance, healthcare
Common Search/ComparisonYesYes

Home Based Python Machine Learning and Data Analyst roles share overlapping skills like data handling and analysis tools. However, Python Machine Learning focuses more on developing algorithms and models using Python, while Data Analysts primarily interpret data to generate reports and insights. Both roles are in demand for remote work and require analytical skills, but Python Machine Learning positions often demand more advanced programming and machine learning expertise.

What are popular job titles related to Home Based Python Machine Learning jobs in Conyers, GA?

For Home Based Python Machine Learning jobs in Conyers, GA, the most frequently searched job titles are:

What job categories do people searching Home Based Python Machine Learning jobs in Conyers, GA look for?

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Cities near Conyers, GA with the most Home Based Python Machine Learning job openings:

Home Based Python Machine Learning jobs near you

Machine Learning Engineer

Five and Fly, LLC.

Atlanta, GA • On-site

Full-time

Re-posted 27 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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