- 1.NLP Engineers earn a median salary of $108,020 with 36% projected growth and 20,800 annual openings (BLS)
- 2.Education: Bachelor's in Data Science or Master's in Data Science typically required
- 3.No state licensing required; certifications like Google Data Analytics Certificate enhance competitiveness
- 4.Top states by salary: California ($145,827), New York ($124,223), Massachusetts ($120,982), Washington ($118,822)
- 5.Process takes 4 years including education plus certification preparation
What Is a NLP Engineer?
A nlp engineer is a professional who analyzes complex data to help organizations make better decisions using statistical methods and machine learning. With 192,270 jobs nationwide, this is a growing occupation with strong career prospects.
The path to becoming a nlp engineer typically requires Dedicated data science programs combining statistics, CS, and domain knowledge.. To explore artificial intelligence programs, see our comprehensive rankings.
NLP Engineer
SOC 15-2051What Does a NLP Engineer Do? Key Responsibilities
NLP Engineers perform a wide range of duties depending on their work setting and specialization. Core responsibilities include:
- Collect, process, and analyze large datasets
- Build predictive models using machine learning algorithms
- Create data visualizations and dashboards
- Communicate findings to stakeholders
- Develop and maintain data pipelines
- Collaborate with engineering and product teams
How to Become a NLP Engineer: Step-by-Step Guide
Total Time: 4 yearsComplete Bachelor's in Data Science
Dedicated data science programs combining statistics, CS, and domain knowledge.
- Integrated curriculum
- Growing availability
- Industry-aligned
Build Technical Skills
Develop hands-on skills through projects, internships, or bootcamps.
- Complete personal projects
- Contribute to open source
- Build a portfolio
Earn Relevant Certifications
Earn certifications like Google Data Analytics Certificate to enhance your credentials.
- Google Data Analytics Certificate - $39/month
- AWS Machine Learning Specialty - $300
Gain Entry-Level Experience
Start your career in an entry-level nlp engineer position to build practical experience.
- Apply for entry-level positions
- Seek mentorship from experienced professionals
- Build your professional network
- Document your accomplishments
Pursue Specialization & Advancement
Specialize in high-demand areas and pursue leadership opportunities.
- Identify specialization areas
- Pursue advanced certifications
- Consider graduate education
- Develop leadership skills
NLP Engineer Education Requirements: Degrees & Programs
Bachelor's in Data Science
4 yearsDedicated data science programs combining statistics, CS, and domain knowledge.
Advantages
- Integrated curriculum
- Growing availability
- Industry-aligned
Considerations
- Newer programs
- May lack depth in specific areas
Master's in Data Science
1.5-2 yearsAdvanced degree for data science and machine learning roles.
Advantages
- Higher salary
- Advanced techniques
- Research opportunities
Considerations
- Higher cost
- Requires strong math background
NLP Engineer Certifications: Required & Recommended
While not required, certifications can increase salary by $5,000-$15,000 annually and demonstrate expertise.
Recommended Specializations
Google Data Analytics Certificate
GoogleEntry-level certification covering data analysis fundamentals.
AWS Machine Learning Specialty
Amazon Web ServicesValidates ML implementation skills on AWS.
NLP Engineer Skills: What You Need to Succeed
Successful nlp engineers combine strong technical competencies with interpersonal skills.
Technical Skills
Primary languages for data analysis and machine learning.
Database querying and data manipulation.
Building and deploying ML models.
Statistical analysis and hypothesis testing.
Tools & Platforms
Creating insights with tools like Tableau, Power BI, or matplotlib.
Spark, Hadoop, and distributed computing.
NLP Engineer Career Path: Entry to Senior
The nlp engineer career path offers diverse opportunities for advancement. Most professionals start in entry-level roles before advancing to senior positions or specializing.
- Junior Data Analyst (Entry Level): Data analysis and reporting. Salary: $70,213-$86,416.
- NLP Engineer (2-4 years): Building models and driving insights. Median salary: $108,020.
- Senior NLP Engineer (5-7 years): Leading data initiatives. Salary: $129,624-$151,228.
- Lead/Principal (8+ years): Data strategy and team leadership. Salary: $162,030-$183,634.
- Chief Data Officer (10+ years): Executive data leadership. Salary: $194,436+.
NLP Engineer Salary by State: What NLP Engineers Earn
Top Employers Hiring NLP Engineers by State
California
CAWashington
WATexas
TXNew York
NYMassachusetts
MAGeorgia
GAIllinois
ILPennsylvania
PAFlorida
FLOhio
OHNLP Engineer Job Outlook: Growth & Opportunities
NLP Engineer employment is projected to grow 36% from 2025 to 2035, much faster than average. About 20,800 job openings are expected each year.
Strong demand is driven by the explosion of data, AI adoption, and data-driven decision making across industries. Professionals with advanced certifications and specialized skills will have the strongest job prospects.
Best Artificial Intelligence Programs
Coding Bootcamps: An Alternative Pathway
Coding bootcamps offer an accelerated pathway into data science careers. For those considering alternatives to traditional degrees, here's what you need to know about this intensive learning format.
What is a Coding Bootcamp?
A coding bootcamp is an intensive, short-term training program (typically 12-24 weeks) that teaches practical programming skills through hands-on projects. Unlike traditional degrees, bootcamps focus exclusively on job-ready skills and often include career services to help graduates land their first tech role.
Who Bootcamps Are Best For
- Career changers looking to enter tech quickly
- Professionals wanting to upskill or transition roles
- Self-taught developers seeking structured training
- Those unable to commit to a 4-year degree timeline
What People Love
Based on discussions from r/codingbootcamp, r/cscareerquestions, and r/learnprogramming
- Learn Python, SQL, and ML tools employers actually use
- Portfolio of data projects differentiates you from candidates
- Many programs cover both analytics and engineering tracks
- Mentorship from working data scientists is invaluable
- Capstone projects can become talking points in interviews
Common Concerns
Honest feedback from bootcamp graduates and industry professionals
- Data science roles often require master's degrees—bootcamp may not suffice
- Statistics and math foundations may be surface-level
- Entry-level data roles are highly competitive right now
- Some bootcamp projects feel contrived compared to real business problems
- May need to start in analyst role before true data science work
Save $1000 on Springboard Bootcamps
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Programs for Data Science careers:
- Data Science Career Track
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More Bootcamp Resources
NLP Engineer FAQs: Requirements, Salary & Career
Data Sources
Job outlook, education requirements, and employment data for nlp engineers
Wage and employment data by state and metro area
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Taylor Rupe
Co-founder & Editor (B.S. Computer Science, Oregon State • B.A. Psychology, University of Washington)
Taylor combines technical expertise in computer science with a deep understanding of human behavior and learning. His dual background drives Hakia's mission: leveraging technology to build authoritative educational resources that help people make better decisions about their academic and career paths.