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Ai Data Rater Jobs in Atlanta, GA (NOW HIRING)

Datavault AI Inc.

Data Scientist

Atlanta, GA · On-site

$110 - $170/hr

Datavault AI, along with its event-technology subsidiary Event Citadel (formerly CompuSystems ... Quantify model performance: precision, recall, calibration, inter-rater agreement against human ...

Datavault AI Inc.

Data Scientist

Atlanta, GA · On-site

Datavault AI, along with its event-technology subsidiary Event Citadel (formerly CompuSystems ... Quantify model performance: precision, recall, calibration, inter-rater agreement against human ...

Kforce Technology Staffing

Senior Data Analyst

Atlanta, GA · On-site

$82K - $104K/yr

Experience leveraging automation and AI-driven insights for analytics * Strong stakeholder ... and data rates may apply. Carriers are not liable for delayed or undelivered messages. You will ...

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Ai Data Rater information

What is an AI data rater?

An AI Data Rater evaluates and rates AI-generated content, such as search engine results, chat responses, or recommendations, to improve machine learning models. They follow specific guidelines to assess relevance, accuracy, and quality. This role helps refine AI systems by providing valuable feedback to enhance their performance. It typically requires strong analytical skills, attention to detail, and familiarity with the subject matter being rated.

What skills and qualifications are needed to thrive as an AI data rater?

To succeed as an AI Data Rater, you need strong analytical skills, attention to detail, and proficiency in evaluating data quality, typically requiring at least a high school diploma or equivalent. Familiarity with computer systems, web browsers, and proprietary rating platforms is often necessary, and training in data privacy or AI guidelines is sometimes provided. Excellent time management, adaptability, and effective written communication help candidates stand out in this largely remote and independent role. These skills ensure accurate data evaluations, support AI improvement, and enable consistent, high-quality performance.

What does an AI data rater do?

As an AI Data Rater, your main responsibilities include reviewing and evaluating various types of data—such as search queries, images, or social media content—according to detailed guidelines provided by your employer. You will typically work independently, using specialized tools or web-based platforms to rate data quality, relevance, or appropriateness. Attention to detail and consistency are important, as your feedback directly impacts the effectiveness of AI systems. Depending on the employer, you may also participate in training sessions or occasional team meetings to stay updated on the latest guidelines or project requirements.

What are the most commonly searched types of Ai Data Rater jobs in Atlanta, GA?

The most popular types of Ai Data Rater jobs in Atlanta, GA are:

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For Ai Data Rater jobs in Atlanta, GA, the most frequently searched job titles are:

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The top searched job categories for Ai Data Rater jobs in Atlanta, GA are:

What cities near Atlanta, GA are hiring for Ai Data Rater jobs?

Cities near Atlanta, GA with the most Ai Data Rater job openings:

Ai Data Rater jobs near you
Infographic showing various Ai Data Rater job openings in Atlanta, GA as of August 2026, with employment types broken down into 61% Full Time, 22% Part Time, 6% Temporary, and 11% Contract. Highlights an 83% In-person, 6% Hybrid, and 11% Remote job distribution.

Enterprise AI Engineer (GCP)

INFT Solutions Inc

Atlanta, GA • On-site, Remote

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.

Job description

Job Description: Enterprise AI Engineer (GCP)
Location: Remote / Hybrid Focus: Agentic AI, Data Intelligence, and Enterprise Scale
Role Overview
We are looking for a Principal Enterprise AI Engineer to architect and deliver high-impact AI
solutions within the Google Cloud ecosystem. This role is designed for a technical leader who
can bridge the gap between complex data landscapes and autonomous AI systems. You will lead
the development of Agentic AI frameworks and Data Intelligence platforms that drive
significant digital transformation for global enterprise clients.
Core Responsibilities
 Architect Agentic Systems: Design and deploy multi-agent orchestration frameworks
using Vertex AI Agent Builder, LangGraph, or CrewAI to automate complex, multi-step
business workflows.
 Master RAG Architectures: Build and optimize high-performance Retrieval-
Augmented Generation (RAG) systems, ensuring LLMs are grounded in enterprise data
across BigQuery and Databricks.
 Model Strategy & Optimization: Select and fine-tune models within the Gemini 1.5
family, balancing high-reasoning capabilities (Pro) with high-speed efficiency (Flash) for
production-grade latency.
 Legacy Transformation: Lead the strategic migration of legacy analytics logic (e.g.,
SAS environments) into modern, AI-powered cloud architectures.
 GTM Collaboration: Work closely with Go-To-Market (GTM) leadership to translate
technical AI roadmaps into measurable business value for C-suite stakeholders.
Required Skill Requirements
1. Agentic AI & Orchestration
 Framework Mastery: Expert implementation of LangChain, LangGraph, or
LlamaIndex for stateful, autonomous agent development.
 Advanced Prompting: Proficiency in Chain-of-Thought (CoT), ReAct patterns, and
system instruction optimization to ensure reliable model output.
 Function Calling: Experience building custom tools that allow LLMs to interact
securely with enterprise APIs and SQL databases.
2. Data Intelligence & Engineering
 Hybrid Data Ecosystems: Deep experience integrating Google Cloud AI services with
Databricks (Delta Lake) for unified data intelligence.
 Vector Engineering: Proficiency with Vertex AI Vector Search (formerly Matching
Engine) and embedding strategies for large-scale semantic search.
 Data Flow: Skill in building scalable pipelines using Dataflow or Spark to process
unstructured data for AI readiness.
3. LLMOps & Production Engineering
 Evaluation Frameworks: Ability to build automated "LLM-as-a-judge" evaluation
pipelines to track accuracy, faithfulness, and hallucination rates.
 Cloud Infrastructure: Mastery of the Vertex AI suite (Studio, Model Garden, Pipelines)
and Infrastructure as Code (Terraform).
 Programming: Expert-level Python (FastAPI, Pydantic) and advanced SQL.
4. Strategic Governance
 Responsible AI: Implementation of safety filters, PII redaction, and ethical AI
monitoring.
 Business Translation: Ability to convert technical metrics (latency, token costs) into
business KPIs (ROI, process efficiency).
Qualifications
 Experience: 8+ years in Software Engineering or Data Science, with at least 3+ years
focused on production-grade AI/ML.
 Education: B.S./M.S. in Computer Science, AI, or a related quantitative field.
 Certifications: Google Professional Machine Learning Engineer or Professional Cloud
Architect (preferred).
Technology Stack
 AI/ML: Vertex AI, Gemini 1.5 Pro/Flash, PyTorch.
 Data: BigQuery, Databricks, Vertex Vector Search.
 Orchestration: LangGraph, Vertex AI Agent Builder.
 DevOps: GitHub Actions, Terraform, Vertex AI Pipelines.