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Remote Natural Language Processing Engineer Jobs in Arizona

Experience working with chatbot or AI-powered support systems using natural language processing or ... Chandler, AZ - Position can be 100% remote for the right candidate.

... processing, and natural language or voice interfaces. Use AI responsibly within daily engineering ... Phoenix-based hybrid environment preferred, with fully remote options considered for the right ...

New

... processing, and natural language or voice interfaces. Use AI responsibly within daily engineering ... Phoenix-based hybrid environment preferred, with fully remote options considered for the right ...

Knowledge Architect

Chandler, AZ ยท On-site +1

$38 - $40/hr

Experience working with chatbot or AI-powered support systems using natural language processing or AI/ML concepts. * Proven track record of collaborating effectively with cross-functional teams and ...

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Remote Natural Language Processing Engineer information

See Arizona salary details

$46.1K

$85.8K

$132.8K

How much do remote natural language processing engineer jobs pay per year?

As of Jun 17, 2026, the average yearly pay for remote natural language processing engineer in Arizona is $85,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,400.00 and $96,000.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a Remote Natural Language Processing Engineer, and why are they important?

To succeed as a Remote Natural Language Processing Engineer, you need strong programming skills in Python, a solid understanding of machine learning and linguistics, and a relevant degree in computer science or a related field. Familiarity with NLP libraries (such as NLTK, spaCy, or Hugging Face Transformers), cloud platforms, and version control systems is typically required. Excellent problem-solving skills, self-motivation, and effective remote communication are crucial soft skills for this position. These abilities enable engineers to build robust language models, collaborate efficiently across distributed teams, and deliver impactful NLP solutions.

What is the difference between Remote Natural Language Processing Engineer vs Remote Data Scientist?

AspectRemote Natural Language Processing EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in CS, NLP, or related; experience with NLP frameworksBachelor's or Master's in CS, Statistics, or related; experience with data analysis
Work EnvironmentFocus on NLP projects, language models, text analysisBroader data analysis, predictive modeling, data visualization
Industry UsageTech, AI, research, companies developing language-based productsFinance, healthcare, tech, consulting, across various sectors

Remote Natural Language Processing Engineers specialize in language-specific AI models and text analysis, while Remote Data Scientists work on broader data analysis and predictive modeling. Both roles require strong technical skills and often overlap in data handling, but NLP Engineers focus more on language data and models.

What does a Remote Natural Language Processing Engineer do?

A Remote Natural Language Processing (NLP) Engineer specializes in developing systems that enable computers to understand, interpret, and generate human language. They work on tasks such as text classification, sentiment analysis, machine translation, and chatbot creation, often utilizing machine learning and deep learning techniques. Working remotely, they collaborate with data scientists, software engineers, and product teams to build and optimize NLP models for various applications. Their work helps improve the way machines interact with people through written and spoken language.

How do Remote Natural Language Processing Engineers typically collaborate with other team members across different time zones?

Remote Natural Language Processing Engineers often work with cross-functional teams, including data scientists, software developers, and product managers, who may be distributed globally. Effective collaboration usually involves leveraging tools like Slack, Jira, and video conferencing to maintain clear communication and coordinate project updates. Flexibility in scheduling and strong documentation skills are important to ensure everyone stays aligned despite time zone differences. Regular virtual meetings and asynchronous communication help address challenges and keep projects on track.
What are popular job titles related to Remote Natural Language Processing Engineer jobs in Arizona? For Remote Natural Language Processing Engineer jobs in Arizona, the most frequently searched job titles are:
What job categories do people searching Remote Natural Language Processing Engineer jobs in Arizona look for? The top searched job categories for Remote Natural Language Processing Engineer jobs in Arizona are:
What cities in Arizona are hiring for Remote Natural Language Processing Engineer jobs? Cities in Arizona with the most Remote Natural Language Processing Engineer job openings:
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Glendale, AZ โ€ข Remote

Other

Posted 25 days ago


Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

โ€‹

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelorโ€™s or Masterโ€™s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.