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Natural Language Processing Jobs in Connecticut (NOW HIRING)

Staffingine LLC

Generative AI Architect

Orange, CT · On-site

Strong proficiency in Natural Language Processing (NLP) and deep learning techniques for building AI models. * Experience with large language models (LLMs) such as GPT, BERT, and OpenAI's fine-tuned ...

Gartner

Sr. Data Scientist

Stamford, CT · On-site

Natural Language Processing and text mining * Search and Recommendation systems * Prompt engineering, LLM fine-tuning, and model optimization * AI agent architectures and orchestration * Strong ...

Gartner

Sr. Data Scientist

Stamford, CT

Natural Language Processing and text mining * Search and Recommendation systems * Prompt engineering, LLM fine-tuning, and model optimization * AI agent architectures and orchestration * Strong ...

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Natural Language Processing information

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$13

$24

$45

How much do natural language processing jobs pay per hour?

As of Jul 3, 2026, the average hourly pay for natural language processing in Connecticut is $24.23, according to ZipRecruiter salary data. Most workers in this role earn between $16.68 and $28.12 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

Natural Language Processing (NLP) specialists, data scientists, and AI ethics professionals are likely to continue thriving as AI advances, due to their expertise in developing, managing, and overseeing AI systems. These roles require specialized skills in machine learning, programming, and critical thinking that are less easily automated. Continuous learning and certification in AI tools and algorithms can help ensure job security in this evolving field.

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 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.

Is Natural Language Processing a good career?

Natural Language Processing (NLP) is a growing field within artificial intelligence that involves developing algorithms to understand and generate human language. It offers opportunities in industries such as tech, healthcare, and finance, often requiring skills in machine learning, programming, and data analysis. Careers in NLP can be rewarding with high demand for expertise and competitive salaries.

What can I do with Natural Language Processing?

A Natural Language Processing (NLP) professional develops systems that enable computers to understand, interpret, and generate human language. This includes tasks like sentiment analysis, language translation, chatbots, and speech recognition, often using tools such as Python, NLP libraries, and machine learning models. NLP roles require strong programming skills and knowledge of linguistics or data science.

Does NLP pay well?

Natural Language Processing (NLP) specialists typically earn competitive salaries, especially with experience in machine learning, deep learning, and programming languages like Python. Salaries vary by industry, location, and level of expertise but generally reflect the high demand for skills in AI and data analysis.
What are the most commonly searched types of Natural Language Processing jobs in Connecticut? The most popular types of Natural Language Processing jobs in Connecticut are:
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What cities in Connecticut are hiring for Natural Language Processing jobs? Cities in Connecticut with the most Natural Language Processing job openings:
Natural Language Processing jobs near you
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Norwalk, CT • On-site

Other

Posted 11 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

​

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:

  • Bachelor’s or Master’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.

Apply