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Machine Learning Nlp Jobs in Georgia (NOW HIRING)

Intuit

AI Scientist 2

Atlanta, GA · On-site

Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with an emphasis on understanding and ...

Intuit

AI Scientist 2

Atlanta, GA · On-site

Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with an emphasis on understanding and ...

Intuit

AI Scientist 2

Atlanta, GA · On-site

Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with an emphasis on understanding and ...

RITWIK Infotech Inc

AI Architect

Atlanta, GA · On-site

$60.50 - $79.75/hr

Strong knowledge of Machine Learning, Deep Learning, NLP, Computer Vision, and Generative AI. * Experience with Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), prompt engineering ...

Workday

Sr Machine Learning Engineer

Atlanta, GA

$159K - $276K/yr

Knowledge of deep learning and NLP techniques * Experience building Extract Transform Load (ETL) ... for machine learning services * Experience in analyzing the ML algorithms that could be used to ...

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All JobsMachine Learning Nlp JobsMachine Learning Nlp Jobs in Georgia

Machine Learning Nlp information

See Georgia salary details

$31.7K

$103.6K

$165.9K

How much do machine learning nlp jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning nlp in Georgia is $103,638.00, according to ZipRecruiter salary data. Most workers in this role earn between $83,200.00 and $114,800.00 per year, depending on experience, location, and employer.

What is a machine learning NLP?

A Machine Learning NLP job involves developing algorithms and models that enable machines to understand, process, and generate human language. Professionals in this role work with large datasets, train models on text data, and fine-tune natural language processing techniques such as sentiment analysis, text classification, and language translation. They often use machine learning frameworks like TensorFlow, PyTorch, and NLP libraries such as spaCy or Hugging Face Transformers. The goal is to build intelligent applications, including chatbots, search engines, and automated content analysis systems.

What does a machine learning NLP do?

As a Machine Learning NLP specialist, your daily responsibilities often include designing and implementing NLP models, cleaning and preprocessing large text datasets, and experimenting with algorithms to improve model performance. You may also evaluate model results, collaborate with software engineers and data scientists, and stay updated on the latest research in the field. Frequent code reviews, participation in team meetings, and contributing to documentation are also common. This role combines hands-on technical work with collaborative problem-solving to develop language-based AI solutions for real-world applications.

What are the key skills and qualifications needed to thrive in the machine learning NLP position?

To thrive as a Machine Learning NLP professional, you need a strong background in machine learning, natural language processing, data analysis, and proficiency in programming languages such as Python, typically supported by a relevant degree in computer science or related field. Familiarity with NLP libraries (like spaCy, NLTK, or Hugging Face), machine learning frameworks (such as TensorFlow or PyTorch), and experience with cloud platforms are highly valued, and certifications can enhance your profile. Strong problem-solving skills, effective communication abilities, and adaptability are important soft skills in this role. These competencies enable you to build sophisticated language models and efficiently collaborate on cross-functional projects in a rapidly evolving technical landscape.

Are machine learning NLP engineers in demand?

Machine learning NLP engineers are in high demand due to the growing use of natural language processing in applications like chatbots, virtual assistants, and data analysis. Companies seek professionals skilled in deep learning frameworks, Python, and NLP tools to develop and improve AI language models, making this a strong career field with positive job growth prospects.

What are popular job titles related to Machine Learning Nlp jobs in Georgia?

For Machine Learning Nlp jobs in Georgia, the most frequently searched job titles are:

What job categories do people searching Machine Learning Nlp jobs in Georgia look for?

The top searched job categories for Machine Learning Nlp jobs in Georgia are:

Machine Learning Nlp jobs near you
Infographic showing various Machine Learning Nlp job openings in Georgia as of August 2026, with employment types broken down into 1% As Needed, 69% Full Time, 21% Part Time, 6% Contract, and 3% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $103,638 per year, or $49.8 per hour.

AI Scientist 2

Intuit

Atlanta, GA • On-site

Full-time

Re-posted 12 days ago

Intuit rating

8.2

Company rating: 8.2 out of 10

Based on 92 frontline employees who took The Breakroom Quiz

107th of 245 rated software companies

Job description

We are seeking an AI Scientist to work with our collaborative and creative group of scientists and engineers to design and implement the next generation AI and machine learning systems that will power our omnichannel marketing platform. In this role, you will develop and deploy modern machine learning and AI models directly in our core product to address key customer challenges. We are looking for someone passionate about the full model development lifecycle, eager to collaborate with product managers to shape innovative AI product experiences, and driven to make a significant impact on our customers.
Responsibilities
  • Explore, develop, and deploy machine learning models, contributing to the end-to-end ML lifecycle in partnership with machine learning engineers and guided by senior scientists.
  • Apply various machine learning techniques (supervised, unsupervised, reinforcement learning, NLP, GenAI) to improve relevance and personalization algorithms, with an emphasis on understanding and implementing solutions that support broader AI initiatives.
  • Collaborate with product managers, software engineers, and designers in designing experiments and minimum viable products, learning to integrate insights from advanced AI systems.
  • Discover, process, and train on huge data sets.
  • In partnership with product managers and analysts, run regular A/B tests, perform statistical analysis, draw conclusions on the impact of your models, and communicate results to peers and leaders.
  • Research and explore new technology shifts, particularly in generative AI and advanced ML, to understand their potential connection with customer benefits and inform ongoing AI strategy.

Qualifications
  • MS, or PhD in an appropriate technology field (Computer Science, Statistics, Applied Math, Operations Research, etc.) or equivalent work experience.
  • 1+ years of experience in modern AI/ML tools and proficient in Python and typical AI/ML libraries (e.g., TensorFlow, PyTorch, Keras). Familiarity with distributed computing frameworks (e.g., Spark, Ray) is a plus.
  • 1+ years of experience in machine learning techniques such as classification, regression, neural networks, large language models, recommender systems, natural language processing, clustering, anomaly detection, and computer vision. Understanding of MLOps principles and practices (e.g., version control, CI/CD for ML models) is a plus.
  • Familiar with the latest trends and applications of generative AI including agentic applications.
  • Efficient in SQL
  • Comfortable in a Linux environment
  • Solid communication skills: Demonstrated ability to explain complex technical issues to both technical and non-technical audiences.

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Intuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at ). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.

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