ZipRecruiter

Log In

1

Hugging Face Jobs in Decatur, GA (NOW HIRING)

Rivian

Staff Security Engineer - AI Security

Atlanta, GA · On-site

$140K - $175K/yr

You are familiar with modern ML frameworks (like PyTorch, Hugging Face, or LangChain) and bring practical experience utilizing specialized AI red teaming tools (such as Garak or PyRIT). * Courage ...

Career Renew

Senior Machine Learning Engineer

Atlanta, GA · Remote

$165K - $225K/yr

... 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 ...

IHG Hotels & Resorts

Principal AI Engineer

Atlanta, GA · On-site

Expert-level proficiency in Python and common AI/ML libraries (e.g., TensorFlow, PyTorch, LangChain, Hugging Face). * Expert experience with a major cloud provider (GCP, AWS, Azure), including their ...

Patientco

Senior ML Engineer I

Atlanta, GA

$100K - $138K/yr

Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). * Solid understanding and hands-on experience with core NLP techniques and ...

JLL

Lead AI Engineer

Atlanta, GA · On-site

$98K - $129K/yr

Demonstrated proficiency in using AI frameworks like LangChain, LlamaIndex, and Hugging Face ecosystem * Demonstrated proficiency with Python development and AI/ML libraries * Demonstrated ...

Crew Career Center

Senior ML Engineer I

Atlanta, GA · On-site

$100K - $138K/yr

Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, Hugging Face Transformers). * Solid understanding and hands-on experience with core NLP techniques and ...

Kaleris

AI SENIOR SOLUTIONS ARCHITECT

Alpharetta, GA · On-site

TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers. * GenAI orchestration tools: LangChain, Semantic Kernel, LlamaIndex; experience with prompt engineering and RAG architecture design.

Verizon

Principal Data Scientist

Alpharetta, GA · On-site

Proven ability to leverage Hugging Face packages and apply the latest machine learning research from Git repositories to real-world projects. * Background in traditional software development ...

next page

Showing results 1-20

All JobsHugging Face JobsHugging Face Jobs in Decatur, GA

Hugging Face information

See Decatur, GA salary details

$8

$15

$20

How much do hugging face jobs pay per hour?

As of Jun 9, 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 professions make 500,000 a year?

Professions that can earn $500,000 or more annually include senior roles such as CEOs, investment bankers, specialized surgeons, and successful entrepreneurs. High earnings often require extensive experience, advanced skills, and often involve leadership or highly specialized knowledge in their fields.

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 job categories do people searching Hugging Face jobs in Decatur, GA look for? The top searched job categories for Hugging Face jobs in Decatur, GA 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
Machine Learning Engineer - LLMs and Agentic

Machine Learning Engineer - LLMs and Agentic

Oversight Systems Inc

Atlanta, GA • On-site

Full-time

Posted 21 days ago

Job description

About Oversight

Oversight is the world’s leading provider of AI-based spend management and risk mitigation solutions for large enterprises. Based in Atlanta, GA, Oversight works with many of the world’s most innovative companies and government agencies to digitally transform their spend audit and financial control processes.

Oversight’s AI-powered platform works across our customers’ financial systems to continuously monitor and analyze all spend transactions for fraud, waste, and misuse. With a consolidated, consistent view of risk across their enterprise, customers can prevent financial loss and optimize spend while strengthening the controls that improve compliance. Learn More.

Position Overview:

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.


Education, Experience and Skills

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.