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Natural Language Understanding Jobs (NOW HIRING)

DabKick

Speech Recognition Engineer

San Jose, CA

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 ...

Standard Template Labs

AI Engineer

New York, NY · On-site

$160K - $230K/yr

You will work on problems such as natural language understanding of IT tickets, dynamic knowledge extraction, intelligent workflow automation, and predictive insights from complex IT infrastructure ...

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 ...

Autodesk

Sr Principal Applied AI Engineer

Kansas, OK

$99.90K - $137.80K/yr

This is a unique senior technical leadership role for someone who can operate across natural language understanding, computer vision, multimodal AI, and agentic systems, while staying grounded in the ...

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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 May 30, 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 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.

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
Conversational AI Developer

Conversational AI Developer

Noblesoft Technologies

Adelphi, MD • Remote

Contractor

Posted 10 days ago

Job description

Role: Conversational AI Developer

Location: Adelphi, Maryland – Hybrid/Remote

Duration: 12+ months

Local candidates preferred

Need LinkedIn profile

Must Have: Chatbot developers Microsoft Foundary

Job Summary

We are seeking a talented and passionate Conversational AI Developer to join our team and play a key role in creating innovative and engaging chatbots and virtual assistants.  The ideal candidate will have a strong background in software development, with a focus on AI and natural language processing technologies.

Responsibilities:

  • Drive the full lifecycle development — from design to deployment — of scalable chatbots and virtual assistants utilizing Microsoft Bot Framework, Kore.ai, or similar CAI technologies
  • Collaborate with cross-functional teams (product managers, designers, UX/UI specialists) to gather requirements, design conversational flows, and implement user stories
  • Integrate Natural Language Processing (NLP) and Natural Language Understanding (NLU) techniques to enable chatbots to understand user intent and respond accordingly
  • Leverage Generative AI services to enhance chatbot responses with creativity and personalization
  • Develop chatbots for deployment across multiple channels (web, mobile apps, messaging platforms) ensuring a seamless user experience
  • Conduct thorough testing and debugging to ensure high performance and accuracy of conversational AI solutions
  • Monitor and analyze user interactions and chatbot performance to identify areas for improvement and optimization
  • Stay updated on the latest advancements in Conversational AI technologies and best practices

Preferred Qualifications:

  • 3+ years of experience in software development, preferably with a focus on conversational AI or chatbots
  • Deep expertise in Azure Bot Framework v4, specifically utilizing Adaptive Dialogs, Waterfall Dialogs, and middleware customization
  • Strong backend development skills with advanced proficiency in C#, .NET, JavaScript, CSS, HTML for custom bot logic
  • Hands-on experience with Azure Integration Services, using Azure Functions and Logic Apps to orchestrate workflows between the bot and external systems
  • Proven experience with Salesforce API integrations (REST/SOAP), specifically for managing Live Agent handoffs, Knowledge base retrieval, and Case creation
  • Experience configuring Azure Cosmos DB for storing conversation state, user data, and telemetry logs
  • Experience implementing Hybrid AI strategies, bridging classical NLU services (Azure CLU) with Generative AI models (Azure OpenAI/GPT) for fall-back handling or content generation
  • Middleware familiarity, with exposure to MuleSoft or similar ESB platforms for enterprise-grade data exchange
  • Data-driven optimization skills, utilizing Power BI to analyze conversation logs, identify drop-off points, and drive NLU accuracy improvements
  • SDLC leadership experience, including defining CI/CD pipelines for bot deployment across multiple environments (Dev/Test/Prod)
  • Excellent communication, collaboration, and problem-solving skills
  • Ability to work independently and manage multiple projects simultaneously
  • Passion for innovation and a strong desire to push the boundaries of Conversational AI technology

Benefits:

  • Be a part of a cutting-edge team at the forefront of Conversational AI development in Higher Education
  • Work on challenging and rewarding projects that make a real impact
  • Opportunity to learn and grow your skills in a dynamic and fast-paced environment