Salary for Senior-level / Expert NLP Engineer in United States during 2023

Salary details

The average senior-level / expert NLP Engineer salary lies between USD 160,000 and USD 235,000 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: Oct. 28, 2024

Top 20 Job Tags for Senior-level / Expert NLP Engineer roles

The three most common job tag items assiciated with senior-level / expert NLP Engineer job listings are Machine Learning, NLP and PyTorch. 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:

Machine Learning | 17 jobs NLP | 17 jobs PyTorch | 14 jobs Python | 12 jobs Engineering | 10 jobs Computer Science | 9 jobs LLMs | 9 jobs Research | 8 jobs Architecture | 8 jobs Classification | 8 jobs TensorFlow | 7 jobs Pipelines | 7 jobs AWS | 6 jobs Deep Learning | 5 jobs Scikit-learn | 5 jobs PhD | 5 jobs Mathematics | 5 jobs Open Source | 4 jobs Keras | 4 jobs SQL | 4 jobs

Top 20 Job Perks/Benefits for Senior-level / Expert NLP Engineer roles

The three most common job benefits and perks assiciated with senior-level / expert 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 | 12 jobs Health care | 7 jobs Startup environment | 7 jobs Flex hours | 6 jobs Home office stipend | 6 jobs Equity / stock options | 5 jobs Flex vacation | 5 jobs 401(k) matching | 3 jobs Competitive pay | 3 jobs Salary bonus | 3 jobs Team events | 2 jobs Parental leave | 1 jobs Wellness | 1 jobs Insurance | 1 jobs Unlimited paid time off | 1 jobs Paid sabbatical | 1 jobs

Salary Composition for Senior NLP Engineers

The salary for a Senior NLP Engineer in the United States typically comprises several components: a fixed base salary, performance-based bonuses, and additional remuneration such as stock options or equity, especially in tech companies. The base salary is the largest component, often accounting for 70-80% of the total compensation package. Bonuses can vary significantly depending on the company’s performance and individual contributions, usually ranging from 10-20% of the base salary. Additional remuneration, such as stock options, is more common in larger tech companies or startups and can be a significant part of the compensation, especially in high-growth industries or regions like Silicon Valley. In contrast, companies in other regions or industries might offer less in terms of equity but compensate with higher base salaries or bonuses.

Steps to Increase Salary Further

To increase your salary beyond the median for a Senior NLP Engineer, consider the following strategies:

• Specialize in High-Demand Areas: Focus on niche areas within NLP, such as conversational AI, sentiment analysis, or multilingual processing, which are in high demand.
• Leadership Roles: Transition into leadership or managerial roles, such as an NLP team lead or head of AI, which typically offer higher compensation.
• Continuous Learning: Stay updated with the latest advancements in NLP and AI technologies, and consider publishing research or contributing to open-source projects to enhance your reputation.
• Networking: Build a strong professional network within the AI/ML community to learn about higher-paying opportunities and gain insights into industry trends.

Educational Requirements

Most Senior NLP Engineer positions require at least a Master’s degree in Computer Science, Data Science, Computational Linguistics, or a related field. A Ph.D. is often preferred, especially for roles that involve research and development of new NLP algorithms or models. Strong academic credentials can significantly enhance your prospects in this field.

Helpful Certifications

While not always mandatory, certain certifications can bolster your credentials and demonstrate expertise in NLP and related areas:

• Certified AI Engineer: Offered by various institutions, this certification covers a broad range of AI topics, including NLP.
• TensorFlow Developer Certificate: Demonstrates proficiency in using TensorFlow, a popular framework for building NLP models.
• AWS Certified Machine Learning – Specialty: Validates your ability to design, implement, and maintain machine learning solutions on AWS, which is valuable for cloud-based NLP applications.

Required Experience

Typically, a Senior NLP Engineer is expected to have 5-10 years of experience in AI/ML, with a significant portion dedicated to NLP. Experience should include hands-on work with NLP libraries and frameworks, such as NLTK, spaCy, or Hugging Face Transformers, and a proven track record of deploying NLP models in production environments. Experience in leading projects or teams is also highly valued.

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