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Nlp Developer Jobs (NOW HIRING)

Hatch IT

NLP/Linguistics Software Engineer

Somerville, MA

$125K - $150K/yr

T. is partnering with Babel Street to find an NLP/Linguistics Software Engineer . Please see details below: About the Role Babel Street is looking for a Software Engineer to join their Analytics ...

Axle

Data Science Fellow - AI/NLP

Rockville, MD

With experts in biomedical science, software engineering, and program management, we focus on ... Data Science Fellow - AI/NLP To be considered for this position, please upload a document as your ...

Babel Street

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

This is an execution-focused "builder" role for an engineer early in their career who wants to work at the intersection of NLP algorithms, search engines, and data science techniques. In this role ...

Babel Street

NLP/Linguistics Software Engineer

Somerville, MA · On-site

$125K - $150K/yr

This is an execution-focused "builder" role for an engineer early in their career who wants to work at the intersection of NLP algorithms, search engines, and data science techniques. In this role ...

Machinify

Staff Data Scientist | NLP

$180K - $230K/yr

Design and train NLP models for tasks like classification, entity extraction, retrieval ... Partner with ML engineers to productionize models (latency, cost, monitoring, drift detection)

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How much do nlp developer jobs pay per hour?

As of Jul 24, 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.

What is a NLP developer?

An NLP developer is a software professional who designs and implements natural language processing systems that enable computers to understand, interpret, and generate human language. They typically work with machine learning models, programming languages like Python, and NLP libraries such as NLTK or spaCy to develop applications like chatbots, language translation, and sentiment analysis.

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 organizations prioritize automation and data analysis.

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 is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as an AI executive, senior researcher, or lead developer, often requiring advanced skills in machine learning, deep learning, and data science. These roles usually involve significant responsibility, expertise in programming languages like Python, and experience with AI frameworks, and they often offer compensation packages including salary, bonuses, and stock options. Such high salaries are rare and usually found in top tech companies or startups with substantial AI initiatives.

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. Achieving this level typically requires specialized expertise, leadership roles, and a strong track record of impact.

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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Infographic showing various Nlp Developer job openings in the United States as of July 2026, with employment types broken down into 83% Full Time, 3% Part Time, 1% Temporary, and 13% Contract. Highlights an 80% Physical, 5% Hybrid, and 15% Remote job distribution, with an average salary of $109,905 per year, or $52.8 per hour.
NLP/Linguistics Software Engineer

NLP/Linguistics Software Engineer

Hatch IT

Somerville, MA

$125K - $150K/yr

Full-time

Posted yesterday

Job description

hatch I.T. is partnering with Babel Street to find an NLP/Linguistics Software Engineer. Please see details below:

About the Role

Babel Street is looking for a Software Engineer to join their Analytics Group. This is an execution-focused "builder" role for an engineer early in their career who wants to work at the intersection of NLP algorithms, search engines, and data science techniques. In this role, you will help create the next generation of architecture and components for their analytics platform, focusing specifically on their record matching functionality. You will bridge the gap between linguistic theory and practical AI applications, helping us implement practical, innovative text analytics and AI-driven features. You will work closely with senior engineers to learn how to deliver software that is safe, reliable, and production-ready.

About the Company

Babel Street is the trusted technology partner for the world's most advanced identity intelligence and risk operations. They deliver advanced AI and data analytics solutions providing unmatched, analysis-ready data regardless of language, proactive risk identification, 360-degree insights, high-speed automation, and seamless integration into existing systems. Babel Street empowers government and commercial organizations to transform high-stakes identity and risk operations into a strategic advantage.  The actionable insights we deliver safeguard lives and protect critical assets around the world.  Babel Street is headquartered in Reston, Virginia, with regional offices in Boston, MA and Cleveland, OH, and international offices in Australia, Canada, Israel, Japan, and the U.K.

What you will do:
  • Implement and Maintain: Write high-quality, maintainable code to support the analytics platform and its record matching components.
  • Bridge Theory and Practice: Take theoretical ideas from linguistics and data science and implement them as practical software features.
  • Support Search Internals: Help optimize and maintain search engine components, including Elasticsearch data modeling and performance tuning.
  • Collaborate and Learn: Participate in agile sprint planning and work daily with senior partners to translate project requirements into technical solutions.
  • Build Scalable Systems: Assist in designing and shipping robust APIs and scalable architectures that integrate into our AI-native platform.
What you will bring:

Required:

  • 2-4 years of professional software engineering experience (including high-impact internships or projects).
  • Proficiency in Java (our core analytics language) or Python (for AI/ML integrations).
  • Problem Solver: Ability to work across teams and make steady progress in ambiguous problem spaces.
  • Educational Foundation: Bachelor's degree in Computer Science, Linguistics, or a related technical field.

Preferred (Nice to Have):

  • Foundation in Data Science: Experience with data quality evaluation, data annotation, or guideline design, preferably for linguistics.
  • Familiarity with Elasticsearch internals or other search/retrieval-based systems.
  • Exposure to computational linguistics or natural language processing (NLP).
  • Interest in Kubernetes and cloud-native architectures.
What success looks like:
  • Month 1-2: Ramp up on the analytics stack and record matching architecture; ship your first initial changes to production.
  • Month 3-4: Take ownership of a specific component or pipeline improvement with guidance, including full testing and documentation.
  • Month 5-6: Deliver a measurable improvement to record matching quality or pipeline reliability and contribute to team design discussions.
Why this role matters:
The record matching functionality is where Babel Street's signals become usable intelligence. Do you care about provenance, explainability, and trust? When a match decision affects whether someone is onboarded or investigated, "the model said so" is not good enough. You will help build systems where every match is defensible, auditable, and tunable - a rare luxury in modern ML-heavy stacks. Do you speak multiple languages? Since our platform processes data from around the globe, your linguistic insights can directly inform how we build and polish the NLP and computational linguistics components that make our record matching world-class.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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