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Hugging Face Jobs in Decatur, GA (NOW HIRING)

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

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)

Elevance Health

Gen AI Engineer

Atlanta, GA · Hybrid

Demonstrated 4+ years hands-on experience with Python, SQL, Hugging Face, TensorFlow, Keras, PyTorch, and Spark. * Experience with GCP/AWS cloud platforms. * Strong knowledge of and measurable hands ...

McKesson

Senior AI Full stack Software Engineer

Atlanta, GA · On-site +1

$131K - $218K/yr

Familiarity with OpenAI, Hugging Face,PyDanticAI, TensorFlow,PyTorch, and healthcare-specific AI libraries. * Communication & Leadership: Ability to communicate complex AI concepts to clinical and ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face ...

McKesson

Senior AI Full stack Software Engineer

Atlanta, GA · On-site +1

$131K - $218K/yr

Familiarity with OpenAI, Hugging Face,PyDanticAI, TensorFlow,PyTorch, and healthcare-specific AI libraries. * Communication & Leadership: Ability to communicate complex AI concepts to clinical and ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Hands on experience with ML frameworks and libraries (Scikit-learn, Pytorch, Tensorflow, LightGBM, Keras, MLFlow etc.) and familiarity with LLM-specific frameworks (e.g., LangChain, Hugging Face ...

MCKESSON

Senior AI Full stack Software Engineer

Atlanta, GA · On-site +1

$131K - $218K/yr

Familiarity with OpenAI, Hugging Face, PyDantic AI, TensorFlow, PyTorch, and healthcare-specific AI libraries. * Communication & Leadership: Ability to communicate complex AI concepts to clinical and ...

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How much do hugging face jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for hugging face in Decatur, GA is $15.09, according to ZipRecruiter salary data. Most workers in this role earn between $12.69 and $17.84 per hour, depending on experience, location, and employer.

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

What are popular job titles related to Hugging Face jobs in Decatur, GA? For Hugging Face jobs in Decatur, GA, the most frequently searched job titles are:
What cities near Decatur, GA are hiring for Hugging Face jobs? Cities near Decatur, GA with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Decatur, GA as of July 2026, with employment types broken down into 79% Full Time, 20% Part Time, and 1% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $31,390 per year, or $15.1 per hour.

Machine Learning Engineer

Five and Fly

Atlanta, GA • On-site

Full-time

Re-posted 15 days ago

Job description

Machine Learning Engineer
Department: Machine Learning Engineer
Employment Type: Full Time
Location: Atlanta, GA
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.
Key Responsibilities
  • 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).
  • 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.
  • 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.
  • 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.

Skills, Knowledge and Expertise
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.
  • 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.

Seeking following AFSC/MOSs
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3D0X4 / 1D7X1 (Software / Data Ops variants)
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US Space Force:Cyber Operations (DCO/OCO) Guardians

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