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Natural Language Processing Jobs in New York (NOW HIRING)

JPMorganChase

Applied AI ML-Senior Associate

Manhattan, NY · On-site

$65K - $65K/yr

Responsibilities : • Apply deep natural language processing (NLP) knowledge & experience and critical thinking skills and perform advanced analytics with the goal of solving complex and multi ...

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$15

$27

$52

How much do natural language processing jobs pay per hour?

As of Jun 14, 2026, the average hourly pay for natural language processing in New York is $27.87, according to ZipRecruiter salary data. Most workers in this role earn between $19.18 and $32.36 per hour, depending on experience, location, and employer.

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.

Will AI replace NLP?

As a natural language processing (NLP) professional, AI is a tool that enhances NLP capabilities rather than replacing the field entirely. Advances in machine learning and deep learning continue to improve NLP applications, but human expertise remains essential for developing, training, and fine-tuning these systems. NLP specialists are expected to adapt and work alongside AI technologies to create more accurate and context-aware language models.

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.

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 jobs are there in NLP?

Jobs in Natural Language Processing (NLP) include roles such as NLP Engineer, Data Scientist, Machine Learning Engineer, Computational Linguist, and Research Scientist. These positions typically require skills in programming, machine learning, and linguistics, and often involve working with tools like Python, TensorFlow, or spaCy to develop language models and algorithms.

Is NLP 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. Careers in NLP typically require a strong educational background and proficiency with tools like Python and TensorFlow.
What are the most commonly searched types of Natural Language Processing jobs in New York? The most popular types of Natural Language Processing jobs in New York are:
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What cities in New York are hiring for Natural Language Processing jobs? Cities in New York with the most Natural Language Processing job openings:
Natural Language Processing jobs near you
Infographic showing various Natural Language Processing job openings in New York as of June 2026, with employment types broken down into 87% Full Time, 8% Part Time, 2% Temporary, and 3% Contract. Highlights an 91% Physical, 1% Hybrid, and 8% Remote job distribution, with an average salary of $57,969 per year, or $27.9 per hour.

AI Developer Natural Language Processing Machine Learning AWS

Accord Technologies Inc.

New York, NY • On-site

Contractor

Posted 9 days ago

Job description

AI Developer – Natural Language Processing,  Machine Learning & AWS 
Loction: New York, NY  (Need Onsite day 1, hybrid 3 days from office).
Duraiton: Long term
Position type: W2 contract

Job Description:

We are seeking a highly skilled and motivated AI Developer specializing in Natural Language Processing (NLP) and Large Language Models (LLMs) to join our dynamic team. The ideal candidate will have strong hands-on experience in implementing LLMs, managing machine learning pipelines, and deploying AI solutions on cloud and server environments. Experience in the financial sector, particularly in equities, will be considered an advantage. 

Responsibilities:

  • Develop, implement, and optimize NLP solutions utilizing LLMs tailored for financial data and equities
  • Manage and deploy Machine Computing Platforms (MCP) to support scalable AI workloads.
  • Collaborate with data scientists and engineers to integrate AI models into production environments.
  • Maintain and enhance AI infrastructure on AWS cloud services and Linux-based servers.
  • Apply traditional machine learning techniques on structured large datasets to complement NLP efforts.
  • Troubleshoot and resolve software/hardware issues related to AI systems and server environments.
  • Stay updated with the latest advancements in NLP, LLMs, and machine learning best practices.

Requirements:

  • Deep knowledge of Natural Language Processing, including expertise with Large Language Models (e.g., GPT, BERT, similar architectures).
  • Hands-on experience in implementing, fine-tuning, and deploying LLMs in production.
  • Proven experience managing and operating MCP or similar machine learning platforms.
  • Strong proficiency with AWS cloud services (EC2, S3, Lambda, etc.) and experience working with Linux server environments.
  • Knowledge of traditional machine learning models applied on structured big data is a plus.
  • Prior experience in equities or financial data analysis is highly preferred.
  • Programming proficiency in Python, and familiarity with relevant AI frameworks (e.g., TensorFlow, PyTorch, Hugging Face).
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment. 
Preferred,
  • Hands-on experience deploying AI models in financial or equities contexts.
  • Familiarity with data pipeline development and big data processing tools.