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Natural Language Understanding Jobs (NOW HIRING)

NTENT

Machine Learning Engineer

Carlsbad, CA

The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ...

NTENT

Machine Learning Engineer

Carlsbad, CA · On-site

The right candidate will work on development, deployment, and lifecycle management of machine learning models for various large-scale applications (natural language understanding, web search and ...

Vantage

Sr. Software Developer - PHP

New Hope, PA

Experience with Machine Learning or Natural Language Understanding algorithms. Benefits: * Medical, Dental and Vision Insurance * 401(k) * Life Insurance * Short-Term and Long-Term Disability * Legal ...

Amazon

Applied Scientist, Core Search

Seattle, WA · On-site

Keyword-based search breaks down when confronted with natural language expressions. Queries like "I ... understanding that customers increasingly expect. Core Search team is reimagining search ...

DabKick

Speech Recognition Engineer

San Jose, CA · On-site

Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences, or Mathematics with specialization in speech recognition, natural language processing, or machine learning Understanding of ...

DabKick

Speech Recognition Engineer

San Jose, CA · On-site

Graduate degree (MS or PhD) in Electrical Engineering, Computer Sciences, or Mathematics with specialization in speech recognition, natural language processing, or machine learning Understanding of ...

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Natural Language Understanding information

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$24.5K

$104.1K

$189.5K

How much do natural language understanding jobs pay per year?

As of Jul 14, 2026, the average yearly pay for natural language understanding in the United States is $104,067.00, according to ZipRecruiter salary data. Most workers in this role earn between $51,500.00 and $145,500.00 per year, depending on experience, location, and employer.

What are the jobs in NLP?

Jobs in Natural Language Processing (NLP) include roles such as NLP Engineer, Data Scientist, Computational Linguist, and Machine Learning Engineer. These positions typically require skills in programming, machine learning, and linguistics, and often involve working with NLP tools and frameworks like Python, TensorFlow, or spaCy.

Is NLP a good career?

Natural Language Processing (NLP) is a growing field within artificial intelligence that involves developing systems to understand and generate human language. Careers in NLP typically require skills in machine learning, programming, and linguistics, and are in demand across industries such as tech, healthcare, and finance. It offers opportunities for innovation, research, and specialization, making it a promising career choice for those interested in AI and language technologies.

Is ML a high paying job?

Machine Learning (ML) roles, including positions like Natural Language Understanding specialists, tend to offer high salaries due to the specialized skills required, such as programming, data analysis, and knowledge of algorithms. Salaries vary based on experience, location, and industry, but overall, ML jobs are considered well-compensated within the tech field.

What are the key skills and qualifications needed to thrive as a Natural Language Understanding (NLU) Engineer, and why are they important?

To thrive as an NLU Engineer, you need a solid background in computational linguistics, machine learning, and programming (typically Python), often supported by a degree in computer science or a related field. Familiarity with NLP frameworks (like spaCy, NLTK, or Hugging Face), deep learning libraries (such as TensorFlow or PyTorch), and experience with large language models are commonly required. Strong analytical thinking, problem-solving skills, and effective collaboration set standout candidates apart. These skills and qualities are crucial for developing accurate, efficient NLU systems that interpret human language for real-world applications.

What are some common challenges faced by professionals working in Natural Language Understanding (NLU) roles?

Professionals in Natural Language Understanding often encounter challenges such as handling the ambiguity and complexity of human language, managing large and diverse datasets, and ensuring models accurately interpret context, sentiment, and intent. Collaborating closely with data scientists, linguists, and software engineers is essential to refine algorithms and improve model performance. Additionally, staying updated with rapid advancements in NLP research and integrating state-of-the-art models into production systems are ongoing aspects of the role.

What is Natural Language Understanding (NLU)?

Natural Language Understanding (NLU) is a subfield of artificial intelligence that focuses on enabling computers to understand, interpret, and respond to human language in a meaningful way. NLU involves processing text or speech input to extract intent, meaning, and context, which allows machines to interact with people naturally. It is commonly used in applications like virtual assistants, chatbots, and translation services to bridge the gap between human communication and computer interpretation.

Does NLP pay well?

Natural Language Understanding roles are generally well-paying within the AI and data science fields, with salaries often reflecting expertise in machine learning, linguistics, and programming skills. Entry-level positions may start lower, but experienced professionals with specialized skills can earn competitive salaries, especially in tech hubs or with advanced certifications.

What is the difference between Natural Language Understanding vs Natural Language Processing?

AspectNatural Language UnderstandingNatural Language Processing
FocusInterpreting and comprehending human languageProcessing and analyzing language data
Skills & CertificationsMachine learning, linguistics, AI certificationsData analysis, programming, NLP tools
Work EnvironmentAI research, tech companies, NLP development teamsData science, software development, AI projects

Natural Language Understanding (NLU) focuses on interpreting the meaning behind human language, enabling machines to comprehend context and intent. In contrast, Natural Language Processing (NLP) encompasses a broader set of techniques for processing, analyzing, and manipulating language data. While NLU is a subset of NLP, both roles often overlap in AI and language technology fields, but NLU emphasizes understanding, whereas NLP includes processing and generation tasks.

More about Natural Language Understanding jobs
What job categories do people searching Natural Language Understanding jobs look for? The top searched job categories for Natural Language Understanding jobs are:
Natural Language Understanding jobs near you
Software Engineer, Siri Attention And Invocation

Software Engineer, Siri Attention And Invocation

Apple

Cupertino, CA • On-site

Full-time

Re-posted 3 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 670 frontline employees who took The Breakroom Quiz

5th of 30 rated technology retailers

Job description

Play a part in the next revolution in human- computer interaction. Collaborate with software engineers as well as machine learning engineers/ scientists in several technical areas spanning the entire range of Siri's capabilities (speech recognition, natural language understanding, dialogue management). Have the opportunity to innovate, create groundbreaking technology, build prototypes of user-facing features and magical experiences, and work with a cross-functional team to ship these magical experiences to millions of users.
Description
The Siri Team is looking for someone with a combination of strong programming skills and a creative, user-focused approach. This role would take Siri to the next level of intelligence and accuracy by using advanced statistical techniques to improve the quality of customer features. This involves working on core machine learning algorithms and systems that are part of Siri's ability to understand and respond to requests. You should be able to thrive in a fast-paced environment with rapidly-changing priorities and technology stacks. A thirst for designing new technology with a user-first approach is crucial.
Minimum Qualifications
Proficiency in object oriented programming (e.g. Swift, C++, or Objective-C)
Excellent algorithm and data structure skills (time and space complexity analysis, optimization, etc.)
Proven to quickly learn and modify large, existing code base
Passion for building demo prototypes and turning them into production quality design/implementation
Strong communication skills to work well with cross-functional engineering teams
Excellent problem solving and critical thinking, good at seeing the big picture
Ability to work in a fast-paced environment with rapidly changing priorities
Enthusiasm for learning and applying data science and machine learning on the job
Preferred Qualifications
B.S. or M.S. degree in Computer Science, or equivalent experience
Passion for high-quality software and excellent user experience
Experience with voice assistant technologies or conversational AI systems
Background in signal processing, natural language processing, or related fields

What Apple employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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