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Nlp Developer Jobs (NOW HIRING)

Brilent

Senior NLP Scientist/Engineer

San Mateo, CA · On-site

... engineers to define product roadmap and feature specifications • Stay current with the latest technological advances in text mining, NLP processing, and machine learning Qualifications • ...

Point72

Quantitative Research Intern (NLP)

New York, NY · On-site

The ideal candidate will have strong machine learning, data science and software engineering skills, some experience with modern NLP, and a curiosity about finance and trading. Responsibilities may ...

United IT

GenAI NLP ML Engineer

Austin, TX

GenAI NLP ML Engineer Location: Austin TX Key Responsibilities: * 10+ yrs experience minimum ... Lead Platform and DevOps: CI/CD, containerization, observability, and environment automation in a ...

Roberts Recruiting

Team Lead NLP Tools

Boston, MA · On-site

We are looking for brilliant software engineers and data scientists with exceptional skills who complement our team. Qualifications: The NLP Tools Team Lead should have the following: * Full stack ...

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How much do nlp developer jobs pay per hour?

As of Jun 15, 2026, the average hourly pay for nlp developer in the United States is $52.84, according to ZipRecruiter salary data. Most workers in this role earn between $40.38 and $64.66 per hour, depending on experience, location, and employer.

Which 3 jobs will survive AI?

NLP developers are likely to continue playing a vital role as AI advances, focusing on designing and improving language models. Jobs that require complex problem-solving, creativity, and emotional intelligence—such as data scientists, AI ethicists, and software engineers—are also expected to persist. These roles involve skills that are difficult for AI to fully replicate, ensuring ongoing demand.

What is a $900,000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior AI researchers or executive positions like AI directors or chief AI officers, often requiring advanced skills in machine learning, deep learning, and data science. These roles usually involve leadership, strategic planning, and extensive experience, and they may be found in large tech companies or specialized AI firms.

What does an NLP Developer do?

An NLP (Natural Language Processing) Developer is a software engineer who designs, builds, and implements applications that allow computers to understand, interpret, and generate human language. They work with large datasets of text or speech, utilizing machine learning, linguistics, and artificial intelligence techniques to create tools such as chatbots, language translators, sentiment analysis systems, and more. NLP Developers often collaborate with data scientists, linguists, and software engineers to improve language models and ensure accurate, efficient processing of natural language data.

Is NLP in high demand?

NLP (Natural Language Processing) is a rapidly growing field within artificial intelligence, with increasing demand for NLP developers across industries such as tech, healthcare, and finance. Skills in machine learning, deep learning, and tools like Python and TensorFlow enhance job prospects, which are expected to remain strong as businesses seek to automate and analyze language data.

What are some common challenges faced by NLP Developers when working with real-world text data?

NLP Developers often encounter challenges such as handling noisy and unstructured data, dealing with ambiguity in human language, and ensuring models generalize well across different domains. Text data from users can contain slang, spelling errors, and mixed languages, requiring careful preprocessing and robust model design. Additionally, NLP Developers must stay updated with evolving language patterns and ensure their solutions are scalable and efficient in production environments.

What engineers make $500,000?

Senior engineers in high-demand fields such as software engineering, data engineering, and machine learning engineering can earn $500,000 or more annually, especially with extensive experience, advanced skills, and working at large tech companies or startups. Compensation often includes base salary, bonuses, and stock options, with roles requiring strong technical expertise and leadership abilities.

What are the key skills and qualifications needed to thrive as an NLP Developer, and why are they important?

To thrive as an NLP Developer, you need a strong background in computer science, linguistics, and machine learning, often supported by a relevant degree or equivalent experience. Familiarity with programming languages like Python, NLP libraries (such as NLTK, spaCy, or Transformers), and frameworks like TensorFlow or PyTorch is essential. Strong analytical thinking, problem-solving abilities, and effective communication skills help you design, implement, and explain complex language models. These skills are crucial for developing accurate, scalable NLP solutions that address real-world language challenges.
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Nlp Developer jobs near you
Infographic showing various Nlp Developer job openings in the United States as of June 2026, with employment types broken down into 33% Full Time, and 67% Contract. Highlights an 81% Physical, 5% Hybrid, and 14% Remote job distribution, with an average salary of $109,905 per year, or $52.8 per hour.

GenAI NLP ML Engineer

United IT Solutions

Austin, TX

Other

Posted 28 days ago

Job description

Role: GenAI NLP ML Engineer
Location: Austin TX
Key Responsibilities :
  • 10+ yrs experience minimum
  • Collaborate and manage with data science, engineering, and GenAI teams to deploy and scale machine learning and generative AI models.
  • Operationalize complex ML and GenAI models into production environments, ensuring end-to-end deployment and monitoring.
  • Apply knowledge of standard ML algorithms (Regression, Classification), NLP concepts (sentiment analysis, topic modeling, TF-IDF), and Generative AI techniques (LLMs, prompt engineering, embeddings).
  • Apply knowledge of Retrieval Augmented Generation using embedding models and Vector databases.
  • Manage delivery of GenAI/LLM features (prompt engineering, evaluation metrics, retrieval patterns, guardrails) and productionizing Q&A/assistant workflows.
  • Lead Platform and DevOps: CI/CD, containerization, observability, and environment automation in a major cloud - ideally working experience on Google.
  • Utilize Python and ML/GenAI libraries such as scikit-learn, PySpark, pandas and Hugging Face Transformers for model development and optimization.
  • Design, develop, and maintain adaptable data pipelines tailored to use-case-specific requirements.
  • Integrate ML and GenAI use cases into business workflows, ensuring seamless data exchange with upstream and downstream systems.
  • Build and maintain pipelines for model performance metrics, supporting Model Risk Oversight and compliance review cadences.
  • Develop runbooks and provide ongoing support for operationalized models to ensure reliability and scalability.

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