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Natural Language Processing Jobs in Arizona (NOW HIRING)

Forhyre

Prompt Engineers

Phoenix, AZ

Stay up-to-date with the latest advancements in natural language processing and AI technologies. * Collaborate with cross-functional teams to integrate prompts into AI applications seamlessly.

Intraedge

Gen AI/ML engineer

Phoenix, AZ · Hybrid

Strong knowledge of machine learning, deep learning, natural language processing, computer vision, and other AI domains. Experience in prompt engineering, data preprocessing, model fine-tuning, and ...

Staffingine LLC

AI ML Engineer

Phoenix, AZ · On-site

$113.70K - $136.50K/yr

Experience with Natural Language Processing NLP * Familiarity with geospatial data and mapping tools * Knowledge of Monte Carlo simulations and stochastic modeling * Experience with Git and CICD ...

Forhyre

Tech Lead - Conversational AI

Phoenix, AZ

In-depth knowledge of natural language processing (NLP), machine learning (ML), and deep learning techniques. * Experience with popular conversational AI platforms and frameworks such as Dialogflow ...

Purple Drive Technologies

Technical Analyst

Phoenix, AZ · On-site

NLP experience (Natural Language Processing). * Regex for data parsing and cleanup. * Strong fundamentals in data transformation and structuring. ITSM Knowledge * Experience working with ServiceNow ...

IntraEdge

Architect

Phoenix, AZ

$63 - $83/hr

... natural language processing, computer vision, or reinforcement learning. • Experience in working with large and complex data sets, and using cloud platforms, such as AWS, Azure, or Google Cloud ...

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How much do natural language processing jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for natural language processing in Arizona is $23.74, according to ZipRecruiter salary data. Most workers in this role earn between $16.35 and $27.55 per hour, depending on experience, location, and employer.

What is a Natural Language Processing job?

A Natural Language Processing (NLP) job involves developing and improving algorithms that enable computers to understand, interpret, and generate human language. Professionals in this field work on tasks like speech recognition, text analysis, machine translation, and chatbot development. They often use machine learning, deep learning, and linguistic principles to build and refine NLP models. NLP experts commonly work in industries such as healthcare, finance, and technology to enhance communication and automate language-related tasks.

What are the key skills and qualifications needed to thrive in the Natural Language Processing position, and why are they important?

To thrive in Natural Language Processing, you need strong expertise in linguistics, statistics, and machine learning, typically supported by a degree in computer science, computational linguistics, or a related field. Familiarity with tools and frameworks such as Python, TensorFlow, PyTorch, spaCy, and NLP libraries, as well as certifications in data science or NLP, are valuable assets. Analytical thinking, problem-solving skills, and the ability to collaborate across multidisciplinary teams are highly desirable. These competencies are essential for developing powerful language models, extracting meaningful insights from data, and delivering effective real-world solutions in language technology.

What are some typical challenges faced by professionals in Natural Language Processing roles?

Professionals in Natural Language Processing (NLP) often encounter challenges such as understanding ambiguities in human language, managing large and unstructured datasets, and keeping up with rapid advances in NLP methodologies. They may also need to fine-tune models for domain-specific contexts and ensure solutions meet ethical and privacy guidelines. Collaboration with data scientists, linguists, engineers, and product teams is common, requiring strong communication skills. Successfully tackling these challenges is a critical part of developing robust NLP applications that add meaningful value to users and businesses.

What kind of jobs use natural language processing?

Natural language processing (NLP) is used in roles such as NLP engineer, data scientist, machine learning engineer, and computational linguist. These jobs involve developing algorithms for language understanding, sentiment analysis, chatbots, and voice recognition systems, often requiring programming skills in Python and familiarity with NLP libraries like NLTK or spaCy.
More about Natural Language Processing jobs
What are the most commonly searched types of Natural Language Processing jobs in Arizona? The most popular types of Natural Language Processing jobs in Arizona are:
What are popular job titles related to Natural Language Processing jobs in Arizona? For Natural Language Processing jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Natural Language Processing jobs in Arizona look for? The top searched job categories for Natural Language Processing jobs in Arizona are:
What cities in Arizona are hiring for Natural Language Processing jobs? Cities in Arizona with the most Natural Language Processing job openings:
Natural Language Processing jobs near you

Data Scientist (PHD Candidates)

Stanley David and Associates

Phoenix, AZ

Other

Posted 13 days ago

Job description

Job Description
Role - Data scientist
Experience Required - 8+ Years
 
We are on the lookout for a specialist in the realm of Artificial Intelligence (AI) and Machine Learning (ML), specializing in Natural Language Processing (NLP), Generative AI and other advanced AI technologies. 
 
Must Have Technical/Functional Skills
 
We are on the lookout for a specialist in the realm of Artificial Intelligence (AI) and Machine Learning (ML), specializing in Natural Language Processing (NLP), Generative AI and other advanced AI technologies. 
Two key requirements for the role:
1. Coding Capability
2. General DS foundations, best to have LLM/GenAI/Agent application building experience
• Extensive experience in building and delivering sophisticated solutions that leverage various AI solutions, machine learning algorithms or technologies and are able to scale optimally.
 
Expert in at least one of the following fields:
o Generative AI
o Machine Learning
o Deep Learning
o Speech Recognition
o Multimodal LLMs
o Reinforcement Learning
o Natural Language Processing
o Optimization
o Probabilistic Inference
o Information Retrieval
o Recommendation Systems
o Bayesian Inference
o Advanced time series forecasting
• Hands-on Experience with most of the following open-source solutions:
o Orchestrate: Airflow, Kubeflow Pipelines, ML Run
o Container: Docker, Kubernetes, Mesos + Marathon
o Model Serving: Kubeflow KF Serving, TF Serving, Seldon-Core, MLflow
o Observability: Prometheus, Grafana, Elasticsearch
• Development:
o Programming Language: Python, Java, Scala, Julia
o IDE: Notebooks, PyCharm, VS Studio
o Machine Learning: TensorFlow, Keras, ScikitLearn, H20.ai, XGBoost, MXNet
o Feature Store: Hopsworks, Feast, or other purposed built Feature Store
o Model Format: ONNX, PMML
• Solid understanding of agile project management principles, with experience leading teams and managing projects in a fast-paced environment.
• Excellent communication and leadership skills, with the ability to collaborate effectively with both technical and non-technical teams.
• Strong problem-solving abilities, with a cre ative and analytical approach to tackling challenges and driving results.
Hands-on Experience with Google Cloud Platform and/or AWS is a plus.
 
 
Roles & Responsibilities
 
• Combine AI/ML and Technology knowledge to implement highly scalable solutions to solve real-world problems in areas such as Generative AI, Personalization, Image Recognition, Speech Recognition, Natural Language Processing, Best Next Action, and Time Series predictions
• Build solutions from identifying business problems, to collecting training dataset, to analyzing data, to modeling, to validating and to delivering production grade solutions at scale.
• Research latest related academic papers and test nascent ideas which can potentially solve new business problems and enhance existing solutions.
• Responsible for developing and defining deployment strategies for production quality AI solutions in Cloud infrastructure at scale
• Drive both high-level and detailed technical designs and conduct design reviews as needed
• Responsible for health and quality of the code across the portfolio, including leadership over innovation, functional testing, and CI/CD tool integration
• Provide technical mentorship to team members at junior levels
• Actively participate in business and technical discussions and forums

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