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Contractual Natural Language Processing Engineer Jobs

Conduct research on cutting-edge techniques in natural language processing (NLP) and machine ... Strong programming skills. * Proficiency with deep learning frameworks such as TensorFlow, PyTorch ...

LLM Research Engineer IV

Mountain View, CA · On-site

$240K/yr

Conduct research on cutting-edge techniques in natural language processing (NLP) and machine ... Strong programming skills. * Proficiency with deep learning frameworks such as TensorFlow, PyTorch ...

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Contractual Natural Language Processing Engineer information

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$49.5K

$113.5K

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

As of Aug 14, 2026, the average yearly pay for contractual natural language processing engineer in the United States is $108,847.00, according to ZipRecruiter salary data. Most workers in this role earn between $113,000.00 and $113,000.00 per year, depending on experience, location, and employer.

What cities are hiring for Contractual Natural Language Processing Engineer jobs?

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What are the most commonly searched types of Natural Language Processing Engineer jobs?

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What states have the most Contractual Natural Language Processing Engineer jobs?

States with the most job openings for Contractual Natural Language Processing Engineer jobs include:

AI Developer ( w / NLP + ML + AWS) : New York, NY : Contract on w2

Marvel Technologies Inc

New York, NY • On-site

Contractor

Re-posted 10 days ago


Job description

The Role:

Our Client is seeking a AI Developer – Natural Language Processing,  Machine Learning & AWS to join our team in New York, NY  (Need Onsite day 1, hybrid 3 days from office).

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, but not required:

  • Hands-on experience deploying AI models in financial or equities contexts.
  • Familiarity with data pipeline development and big data processing tools.