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Meta Design Jobs in Georgia (NOW HIRING)

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Contribute to the design, training, fine-tuning, and deployment of ML/LLM models for production ... Meta LLaMA (fine-tuned/custom models for domain-specific tasks). * Collaborate with Data ...

Invest with Roots

Paid Media Manager

Atlanta, GA · On-site

$119K - $124K/yr

You'll manage campaigns across Google, Meta, Bing, and mobile app acquisition channels, build a ... Design and evaluate experiments across creative, landing pages, onboarding, and acquisition ...

Invest with Roots

Paid Media Manager

Atlanta, GA · On-site

$119K - $124K/yr

You'll manage campaigns across Google, Meta, Bing, and mobile app acquisition channels, build a ... Design and evaluate experiments across creative, landing pages, onboarding, and acquisition ...

Greensky Credit

Senior Data Engineer

Atlanta, GA · On-site

$101K - $138K/yr

Identify, design, and implement internal process improvements: automating manual processes ... profiling meta data, and the data lifecycle process; and using change data capture tools for ...

AmNet Services, Inc.

Project Manager - IV

Alpharetta, GA · On-site

$54.50 - $72.25/hr

We design and manufacture sensors for storage tanks, water metering, energy metering, gas ... meta tags) Tools search engine products (e.g. Endeca, Solr/Lucene, ElasticSearch, FAST or other ...

Varsity Tutors

HTML Tutor

Marietta, GA · Remote

$18 - $40/hr

... meta tags, and integration with CSS and JavaScript. Ability to explain semantic markup, responsive design principles, ARIA roles, and SEO-friendly structure while preparing students for web ...

Varsity Tutors

HTML Tutor

Johns Creek, GA · Remote

$18 - $40/hr

... meta tags, and integration with CSS and JavaScript. Ability to explain semantic markup, responsive design principles, ARIA roles, and SEO-friendly structure while preparing students for web ...

Varsity Tutors

HTML Tutor

Woodstock, GA · Remote

$18 - $40/hr

... meta tags, and integration with CSS and JavaScript. Ability to explain semantic markup, responsive design principles, ARIA roles, and SEO-friendly structure while preparing students for web ...

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Meta Design information

What is meta design?

Meta Design refers to the process of designing systems, frameworks, or methodologies that enable others to create their own designs. It involves creating tools, guidelines, or structures that facilitate creativity and adaptability, rather than producing a single, finished product. Meta Design is often used in fields like user experience, software development, and architecture, where flexibility and user participation are essential. Its goal is to empower users or stakeholders to shape outcomes according to their needs within a well-considered framework.

How does a meta designer typically collaborate with cross-functional teams during the design process?

Meta Designers often work closely with product managers, engineers, researchers, and other designers to ensure that design systems are cohesive and scalable. They facilitate workshops, share design guidelines, and gather feedback from various stakeholders to refine the overarching design framework. Effective communication and collaboration are vital, as Meta Designers need to bridge strategic vision with practical implementation, ensuring consistency across a wide range of products and platforms.

What are the key skills and qualifications needed to thrive as a meta designer, and why are they important?

To thrive as a Meta Designer, you need a strong background in design principles, user experience (UX), and systems thinking, often supported by a degree in design or a related field. Familiarity with design software such as Adobe Creative Suite, Figma, and prototyping tools, as well as knowledge of digital platforms and information architecture, is essential. Creative problem-solving, collaboration, and the ability to communicate complex concepts clearly are key soft skills for this role. These skills ensure that Meta Designers can develop cohesive design systems that adapt across platforms, enhancing user experience and organizational consistency.

What is the difference between Meta Design vs User Experience Designer?

AspectMeta DesignUser Experience Designer
CredentialsDesign degree, portfolio, sometimes certificationsDesign or related degree, portfolio, UX certifications
Work EnvironmentDesign agencies, tech companies, creative teamsTech companies, agencies, product teams
Industry UsageUsed in digital, branding, and interface design projectsFocused on improving user interactions and satisfaction

Meta Design and User Experience Designer roles overlap in design skills and work environments, but Meta Design emphasizes holistic visual and conceptual design strategies, while User Experience Designers focus on optimizing user interactions and usability. Understanding these differences helps clarify career paths and job expectations in the digital design industry.

What are the most commonly searched types of Meta Design jobs in Georgia?

The most popular types of Meta Design jobs in Georgia are:

What are popular job titles related to Meta Design jobs in Georgia?

For Meta Design jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Meta Design jobs in Georgia look for?

The top searched job categories for Meta Design jobs in Georgia are:

What cities in Georgia are hiring for Meta Design jobs?

Cities in Georgia with the most Meta Design job openings:

Meta Design jobs near you
Infographic showing various Meta Design job openings in Georgia as of August 2026, with employment types broken down into 81% Full Time, 8% Part Time, 8% Contract, and 3% Nights. Highlights an 82% Physical, 5% Hybrid, and 13% Remote job distribution.

Machine Learning Engineer

Atlanta, GA • On-site

Five and Fly
See more jobs at Five and Flyexternal

Full-time

Re-posted 19 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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35Q - Cryptologic Network Warfare Specialist
35N / 35P / 35S (Intel Analysts w/ coding exposure)
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1B4X1 - Cyber Warfare Operations
9S100 - Scientific Applications Specialist
3D0X4 / 1D7X1 (Software / Data Ops variants)
US Navy:CTN - Cryptologic Technician (Networks)CTI / CTR (with analytics focus)Information Warfare Officers (1810)
US Marine Corps:1721 - Cyberspace Warfare Operator26XX Intel (with data/automation focus)
US Space Force:Cyber Operations (DCO/OCO) Guardians

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