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Natural Language Processing Intern Jobs in Atlanta, GA

Finastra

AI Engineer Intern (Summer 2027)

Atlanta, GA · On-site +1

As an AI Engineer Intern at Finastra, you will gain hands-on experience working with cutting-edge ... Help develop natural language interfaces and AI-powered tools that simplify access to data and ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

QGenda

Senior Data Engineer

Atlanta, GA · Hybrid

$101K - $138K/yr

Design and deliver AI-ready data products, ensuring data structures, metadata, and pipelines are suitable for natural language processing, predictive analytics, and other AI-driven capabilities Who ...

UNAVAILABLE

AI Implementation Engineer

Alpharetta, GA · On-site

$120 - $160/hr

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

$120 - $180/hr

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

Aptean

AI Implementation Engineer

Alpharetta, GA · On-site

$120 - $170/hr

Experience with advanced natural language processing methods such as classification, entity extraction, and summarization. * Experience developing traditional machine learning models for supply-chain ...

HireITPeople

Senior Cloud AI Architect

Atlanta, GA · On-site

$62.50 - $79.50/hr

... and natural language processing. ● Evaluate and recommend AI platforms, frameworks, and tools (e.g., Azure ML, AWS SageMaker, Google Vertex AI, PyTorch). ● Design secure and compliant AI/ML ...

State Farm

Lead Data Scientist - Gen AI

Dunwoody, GA

It also hosts centers of excellence for natural language processing, experimental design, generative AI, & data science training/research. At State Farm, we believe in fostering professional growth ...

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All JobsNatural Language Processing Intern JobsNatural Language Processing Intern Jobs in Atlanta, GA

Natural Language Processing Intern information

See Atlanta, GA salary details

$8

$16

$22

How much do natural language processing intern jobs pay per hour?

As of Sep 4, 2026, the average hourly pay for natural language processing intern in Atlanta, GA is $16.64, according to ZipRecruiter salary data. Most workers in this role earn between $13.85 and $18.51 per hour, depending on experience, location, and employer.

What is a natural language processing intern?

A Natural Language Processing (NLP) Intern works on projects related to computational linguistics, machine learning, and text analysis. Responsibilities may include preprocessing text data, training and fine-tuning language models, implementing NLP algorithms, and evaluating model performance. Interns typically collaborate with data scientists, engineers, and researchers to improve and deploy NLP solutions for tasks such as sentiment analysis, named entity recognition, or chatbot development. This role requires proficiency in programming languages like Python, familiarity with NLP libraries such as TensorFlow or spaCy, and a strong foundation in machine learning concepts.

What types of projects or tasks does a natural language processing intern typically work on during their internship?

As a Natural Language Processing Intern, you can expect to work on projects such as building or refining text classification models, cleaning and annotating datasets, assisting with the implementation of algorithms for tasks like sentiment analysis or language generation, and analyzing the performance of NLP systems. Interns often collaborate with experienced data scientists, machine learning engineers, and linguists to solve real-world language processing challenges. You may also help research new NLP techniques or work on the integration of models into existing products or services. This hands-on experience provides valuable exposure to practical NLP workflows and is a great stepping stone for a career in AI or machine learning.

What are the key skills and qualifications needed to thrive as a natural language processing intern, and why are they important?

To thrive as a Natural Language Processing Intern, you need a solid background in programming (especially Python), understanding of machine learning concepts, and coursework or experience in linguistics or NLP techniques. Familiarity with NLP libraries such as NLTK, spaCy, or Hugging Face, and experience using platforms like Jupyter Notebooks and version control systems are often required. Strong problem-solving skills, attention to detail, and the ability to communicate technical findings clearly will help you stand out. These skills and qualities enable you to effectively support research, analyze language data, and contribute to NLP projects within collaborative technical teams.

Is natural language processing in demand?

Natural Language Processing (NLP) is a rapidly growing field with increasing demand for professionals, including NLP interns, as businesses seek to improve automation, customer service, and data analysis. Skills in machine learning, Python, and NLP tools like spaCy or NLTK enhance employability in this expanding industry.

What are the most commonly searched types of Natural Language Processing jobs in Atlanta, GA?

The most popular types of Natural Language Processing jobs in Atlanta, GA are:

What are popular job titles related to Natural Language Processing Intern jobs in Atlanta, GA?

For Natural Language Processing Intern jobs in Atlanta, GA, the most frequently searched job titles are:

What job categories do people searching Natural Language Processing Intern jobs in Atlanta, GA look for?

The top searched job categories for Natural Language Processing Intern jobs in Atlanta, GA are:

Natural Language Processing Intern jobs near you
Infographic showing various Natural Language Processing Intern job openings in Atlanta, GA as of August 2026, with employment types broken down into 1% As Needed, 74% Full Time, 20% Part Time, 1% Temporary, and 4% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $34,614 per year, or $16.6 per hour.

Machine Learning Engineer III 4P/791

4P Consulting Inc.

Atlanta, GA

Contractor

Re-posted 4 days ago

Job description

Position:         Machine Learning Engineer III – AI/ML Product Engineering

Location:        Atlanta, GA

Duration:        5 Months
Client:            Southern Company Services

Southern Company Services is seeking an experienced Machine Learning Engineer III to develop scalable, reusable, and production-grade AI products for deployment across multiple operating companies.

This role will focus on Retrieval-Augmented Generation, multi-agent systems, natural language processing, model deployment, and cloud-based AI solutions. The ideal candidate will have strong software engineering skills, hands-on AI/ML experience, and expertise with Azure or Google Cloud Platform.

 

Key Responsibilities

·       Design and build modular, reusable AI components and services.

·       Develop scalable RAG solutions using structured and unstructured data.

·       Engineer multi-agent systems for task coordination, workflow automation, and decision support.

·       Build transcription and NLP pipelines for customer-interaction analysis.

·       Develop and fine-tune models using PyTorch, Hugging Face Transformers, LangChain, or similar frameworks.

·       Package and deploy models using Azure Machine Learning, Google Cloud Platform, or Databricks.

·       Integrate Databricks for data ingestion, feature engineering, experimentation, and model development.

·       Develop reusable libraries, APIs, templates, and engineering patterns.

·       Partner with MLOps, DevOps, data engineering, architecture, and product teams.

·       Implement monitoring for model performance, data drift, system usage, and operational reliability.

·       Ensure AI solutions meet enterprise security, privacy, compliance, scalability, and observability requirements.

·       Provide technical guidance to teams adopting shared AI products and components.

 

Required Qualifications

·       Strong experience developing and deploying production-grade AI and machine learning solutions.

·       Hands-on experience with RAG architectures, LLM applications, multi-agent systems, and NLP.

·       Experience with Azure AI services, Google Cloud Platform AI services, or Azure Machine Learning.

·       Proficiency with Python and frameworks such as PyTorch, Transformers, or LangChain.

·       Experience deploying scalable models and AI services in cloud environments.

·       Knowledge of APIs, software engineering practices, model monitoring, and MLOps.

·       Experience working with structured and unstructured datasets.

·       Strong communication, collaboration, analytical, and problem-solving skills.

 

Preferred Qualifications

·       Experience with Databricks, vector databases, embeddings, and semantic search.

·       Experience building reusable enterprise AI platforms or shared AI services.

·       Knowledge of model evaluation, data drift, observability, and responsible AI.

·       Familiarity with CI/CD, containers, Kubernetes, and cloud-native deployment.

·       Utility, energy, or regulated-industry experience is preferred.