NLP Engineer Salary in United States during 2024

Salary details

The average NLP Engineer salary lies between USD 150,000 and USD 200,000 in the United States. It represents the overall compensation/gross salary amount for the working year (before deductions like social security, taxes and other contributions), not including equity/stock options or similar benefits.

Region represents the primary country of residence of an employee during the year (or residence for tax purposes). All data shown are full-time equivalent (FTE) salaries. Part-time salary information has been extrapolated to its FTE value.

Last updated: Dec. 22, 2024

Salary trend

Top 20 Job Tags for NLP Engineer roles

The three most common job tag items assiciated with NLP Engineer job listings are NLP, Machine Learning and Python. Below you find a list of the 20 most occuring job tags in 2024 and the number of open jobs that where associated with them during that period:

NLP | 49 jobs Machine Learning | 46 jobs Python | 38 jobs LLMs | 33 jobs Engineering | 32 jobs Computer Science | 27 jobs PyTorch | 25 jobs Research | 24 jobs TensorFlow | 21 jobs AWS | 17 jobs Classification | 17 jobs Architecture | 14 jobs ML models | 14 jobs Deep Learning | 13 jobs Git | 12 jobs Statistics | 12 jobs Generative AI | 12 jobs Open Source | 11 jobs Pipelines | 11 jobs spaCy | 10 jobs

Top 20 Job Perks/Benefits for NLP Engineer roles

The three most common job benefits and perks assiciated with NLP Engineer job listings are Career development, Competitive pay and Flex hours. Below you find a list of the 20 most occuring job perks or benefits in 2024 and the number of open jobs that where offering them during that period:

Career development | 36 jobs Competitive pay | 14 jobs Flex hours | 12 jobs Health care | 12 jobs Startup environment | 12 jobs Conferences | 8 jobs Equity / stock options | 7 jobs Team events | 5 jobs Insurance | 5 jobs Salary bonus | 4 jobs Unlimited paid time off | 4 jobs Parental leave | 3 jobs Flex vacation | 3 jobs Wellness | 2 jobs Home office stipend | 1 jobs

Salary Composition for NLP Engineers

The salary for an NLP Engineer in the United States typically comprises a base salary, bonuses, and additional remuneration such as stock options or benefits. The base salary is the fixed component and usually forms the largest part of the total compensation package. Bonuses can vary significantly depending on the company’s performance, individual performance, and industry standards. In tech hubs like Silicon Valley, bonuses and stock options can be substantial, especially in larger tech companies or successful startups. In contrast, smaller companies or those in less competitive regions might offer lower bonuses but could compensate with other benefits like flexible working conditions or professional development opportunities.

Steps to Increase Salary

To increase your salary from the median level, consider the following strategies:

• Skill Enhancement: Continuously update your skills in the latest NLP technologies and tools. Specializing in emerging areas like transformer models or conversational AI can make you more valuable.
• Advanced Education: Pursuing a master's or Ph.D. in a related field can open doors to higher-paying roles.
• Leadership Roles: Transitioning into a managerial or lead position can significantly boost your salary.
• Industry Switch: Some industries, such as finance or healthcare, may offer higher salaries for NLP expertise due to the complexity and value of the data involved.
• Networking: Building a strong professional network can lead to opportunities in higher-paying companies or roles.

Educational Requirements

Most NLP Engineer positions require at least a bachelor's degree in computer science, data science, mathematics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles involving complex research or development tasks. These advanced degrees provide a deeper understanding of machine learning algorithms, statistical methods, and linguistic principles, which are crucial for NLP tasks.

Helpful Certifications

While not always mandatory, certain certifications can enhance your profile:

• Certified Machine Learning Specialist (CMLS)
• TensorFlow Developer Certificate
• AWS Certified Machine Learning – Specialty
• Microsoft Certified: Azure AI Engineer Associate

These certifications demonstrate proficiency in specific tools and platforms commonly used in NLP projects.

Experience Requirements

Typically, employers look for candidates with 2-5 years of experience in machine learning or data science roles, with a focus on NLP projects. Experience with NLP libraries such as NLTK, spaCy, or Hugging Face Transformers, as well as familiarity with deep learning frameworks like TensorFlow or PyTorch, is often required. Experience in deploying NLP models in production environments is also highly valued.

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