NLP Engineer Salary in United States during 2023

Salary details

The average NLP Engineer salary lies between USD 150,000 and USD 210,000 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 2023 and the number of open jobs that where associated with them during that period:

NLP | 38 jobs Machine Learning | 36 jobs Python | 32 jobs Engineering | 26 jobs PyTorch | 22 jobs Computer Science | 21 jobs Research | 17 jobs Classification | 17 jobs LLMs | 16 jobs AWS | 14 jobs Architecture | 14 jobs ML models | 14 jobs Pipelines | 14 jobs Statistics | 14 jobs TensorFlow | 12 jobs SQL | 12 jobs Scikit-learn | 11 jobs Java | 11 jobs Testing | 10 jobs Git | 9 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, Health care and Startup environment. Below you find a list of the 20 most occuring job perks or benefits in 2023 and the number of open jobs that where offering them during that period:

Career development | 30 jobs Health care | 19 jobs Startup environment | 15 jobs Flex hours | 13 jobs Competitive pay | 12 jobs Insurance | 10 jobs Equity / stock options | 7 jobs Flex vacation | 6 jobs Home office stipend | 6 jobs Team events | 5 jobs Salary bonus | 5 jobs 401(k) matching | 4 jobs Lunch / meals | 2 jobs Parental leave | 2 jobs Pet friendly | 2 jobs Unlimited paid time off | 2 jobs Wellness | 1 jobs Transparency | 1 jobs Paid sabbatical | 1 jobs

Salary Composition for NLP Engineers

The salary for an NLP Engineer in the United States typically comprises a base salary, performance bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the fixed component and usually forms the largest part of the total compensation package. Performance bonuses can vary significantly depending on the company's success and individual performance, often ranging from 10% to 20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can significantly increase the total compensation, especially if the company performs well. Regional differences also play a role; for instance, salaries in tech hubs like San Francisco or New York City tend to be higher due to the cost of living and competitive job market. Industry-wise, tech companies, financial services, and healthcare tend to offer higher salaries compared to academia or non-profit sectors.

Steps to Increase Salary

To increase your salary from the current position, 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 up higher-paying opportunities.
• Networking: Engage with professional networks and communities. This can lead to opportunities in higher-paying companies or roles.
• Leadership Roles: Transitioning into managerial or lead roles can significantly increase your salary.
• Switching Companies: Sometimes, moving to a different company can result in a substantial salary increase, especially if the new company values your specific skill set more.

Educational Requirements

Most NLP Engineer positions require at least a bachelor's degree in computer science, data science, linguistics, or a related field. However, a master's degree or Ph.D. is often preferred, especially for roles involving research or advanced model development. Courses in machine learning, artificial intelligence, and natural language processing are particularly beneficial.

Helpful Certifications

While not always required, certain certifications can enhance your resume and demonstrate your expertise:

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

These certifications can validate your skills and knowledge in specific tools and platforms, making you more attractive to potential employers.

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 programming languages like Python, familiarity with NLP libraries such as NLTK, SpaCy, or Hugging Face, and experience in deploying NLP models in production are often required. Experience in related fields like data analysis or software engineering can also be beneficial.

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