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Natural Language Processing Jobs in Hartford, CT

Cigna

Technical Product Manager - Applied AI

Bloomfield, CT · On-site +1

$166K - $192K/yr

Lead the design and development of AI capabilities, including Natural Language Processing (NLP), GenAI, predictive modeling, and agent-based automation. * Build AI-driven workflows that simplify ...

Cigna

Technical Product Manager - Applied AI

Bloomfield, CT · On-site

$166K - $192K/yr

Lead the design and development of AI capabilities, including Natural Language Processing (NLP), GenAI, predictive modeling, and agent-based automation. * Build AI-driven workflows that simplify ...

Pwc

AI & GenAI Data Scientist - Manager

Hartford, CT · On-site

$99K - $232K/yr

... natural language processing Travel Requirements Up to 80% Job Posting End Date The salary range for this position is: $99,000 - $232,000. Actual compensation within the range will be dependent upon ...

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How much do natural language processing jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for natural language processing in Hartford, CT is $25.70, according to ZipRecruiter salary data. Most workers in this role earn between $17.69 and $29.81 per hour, depending on experience, location, and employer.

What is a natural language processing?

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 natural language processing, 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?

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.

How to get a job in Natural Language Processing?

To get a job in Natural Language Processing (NLP), candidates typically need a strong background in computer science, linguistics, or related fields, along with proficiency in programming languages like Python and experience with NLP libraries such as NLTK or spaCy. Gaining practical experience through projects, internships, or research, and obtaining relevant certifications can improve employability. A solid understanding of machine learning, deep learning, and data analysis is also beneficial for NLP roles.

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 linguistics. The demand for NLP professionals is increasing, making it a promising career choice for those interested in AI and language technologies.

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 like Python, NLP libraries, and machine learning techniques. NLP roles require strong programming skills and knowledge of linguistics or data science.

What are popular job titles related to Natural Language Processing jobs in Hartford, CT?

For Natural Language Processing jobs in Hartford, CT, the most frequently searched job titles are:

What job categories do people searching Natural Language Processing jobs in Hartford, CT look for?

The top searched job categories for Natural Language Processing jobs in Hartford, CT are:

Natural Language Processing jobs near you
Infographic showing various Natural Language Processing job openings in Hartford, CT as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 22% Part Time, 1% Temporary, and 4% Contract. Highlights an 90% Physical, 1% Hybrid, and 9% Remote job distribution, with an average salary of $53,448 per year, or $25.7 per hour.

AI Native Full Stack Engineer

3B Staffing LLC

Hartford, CT • Remote

Full-time

Re-posted 16 days ago

Job description

AI Native Full Stack Engineer

REMOTE

CVS

LOCATION: REMOTE

**PLEASE MAKE SURE LINKED IN AND PHOTOS MATCH**

**PLEASE MAKE SURE TO READ THE BELOW IN DETAIL AND PROVIDE THE CORRECT PROFILES**

**THIS MANAGER IS EXTREMELY TOUGH AND PICKY - NEED EXCEPTIONAL COMMUNICATION SKILLS. NO USE OF AI, NEED LEGIT CANDIDATES HERE**

FEEDBACK FROM 1st BATCH:

The profiles you shared are amazing, but as things are evolving a bit here, we need to do some minor course corrections on the nature of profiles we are looking for. Our goal here is to build AI native Applications which will be used in Automation scenarios. Most of these profiles are more suitable for data analytics / data engineering / core ML model refinements etc..

We are looking for four types of engineers which I'd call class I through IV

I: Full stack web development professional who has depth of experience in building Angular Frontend with Python (Fast API) based backends. This engineer should have some experience with ML frameworks, using webservices from OpenAI, Google Vertex AI etc.. and deployment knowledge to get his / her application to GCP.

II: Full stack web development professional who has depth of experience in building Angular Frontend with Java (Springboot) based backends. This engineer may or may not have experience with ML frameworks, using webservices from OpenAI, Google Vertex AI etc.. but has to for sure have deployment knowledge to get his / her application to GCP.

JOB DESCRIPTION:

You will be responsible for designing, developing, and deploying robust and scalable AI Native Applications that leverage artificial intelligence (AI) and machine learning (ML) services and tools. You bring expertise in full-stack web application development using programing languages like Python and JavaScript frameworks such as Angular C React. You have demonstrated experience of fundamentals of machine learning principles, natural language processing (NLP) and principles of Generative AI. You must have experience on Google Cloud Platform (GCP) through the entire application life cycle management through development, deployment, telemetry, logging etc.,

Responsibilities:

  • Design, develop, and maintain AI Native web applications and/or web services to deliver innovative features and functionalities. Eg: Retrival Augmented Generation
  • Utilize Google Cloud Platform (GCP) services (e.g., AI Platform, Vertex AI, BigQuery, Cloud Storage) to build, train, and deploy AI Native Applications.
  • Implement and integrate AI/ML models and ML Services into existing applications and systems using Python and JavaScript.
  • Collaborate with data scientists, product managers, and other engineering teams to translate business requirements into technical solutions.
  • Finetune models on GCP for use case specific needs.
  • Conduct model evaluation, testing, and deployment, ensuring high-quality and reliable AI solutions.
  • Stay updated with the latest advancements in AI, machine learning, and cloud technologies.
  • Working knowledge of Agile Scrum methodologies including document technical designs, processes, and model specifications.
  • Leverage LangChain, LangGraph, ADK, and other agent orchestration frameworks.
  • Implement prompt engineering, chain-of-thought workflows, and retrieval- augmented generation (RAG) pipelines.
  • Develop modular, scalable architectures for AI-powered web apps and APIs.
  • Integrate LLMs with enterprise systems, databases, and external services.
  • Implement vector databases for semantic search.
  • Build connectors for structured/unstructured data ingestion.
  • Work closely with automation teams, architects, and product owners to deliver end-to-end AI solutions.
  • Document workflows and best practices for AI integration.

Qualifications:

  • Bachelor's or Master's degree in Computer Science, Engineering, or related field.
  • 5+ years of experience as an AI Engineer, ML Engineer, or similar role.
  • Strong proficiency in Python (mandatory) and familiarity with

JavaScript/TypeScript.

  • Hands-on experience with LangChain, ADK, and orchestration frameworks.
  • Experience with LLMs (OpenAI, Azure OpenAI, Hugging Face) and prompt engineering.
  • Proficiency in GCP services and SDKs; experience with Azure or AWS is a plus.
  • Strong knowledge of FastAPI/Django, Angular/React, and ML libraries (TensorFlow, PyTorch, scikit-learn).
  • Familiarity with vector databases (Pinecone, Weaviate, FAISS).
  • Experience with containerization (Docker/Kubernetes) and CI/CD pipelines.
  • Good understanding of ML algorithms, deep learning, and statistical analysis.
  • Ability to work independently and collaboratively in Agile environments.
  • Excellent communication and interpersonal skills.

Apply