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Internship Natural Language Processing Jobs in Virginia

Photon

GenAI Solution Architect - VA

Norfolk, VA · On-site

$61 - $80.25/hr

Strong understanding of deep learning, natural language processing, and computer vision. Excellent problem-solving skills and ability to work independently and in a team environment. Preferred ...

All Native Group

Junior Data Scientist

Arlington, VA

Apply natural language processing (NLP) techniques to extract, enrich, and analyze unstructured data. * Improve and expand existing entity extraction processes, incorporating new entities and models ...

All Native Group

Junior Data Scientist

Arlington, VA · On-site

$70 - $95/hr

Apply natural language processing (NLP) techniques to extract, enrich, and analyze unstructured data. * Improve and expand existing entity extraction processes, incorporating new entities and models ...

All Native Group

Junior Data Scientist

Arlington, VA · On-site

Apply natural language processing (NLP) techniques to extract, enrich, and analyze unstructured data. * Improve and expand existing entity extraction processes, incorporating new entities and models ...

All Native Group

Junior Data Scientist

Arlington, VA · On-site

Apply natural language processing (NLP) techniques to extract, enrich, and analyze unstructured data. * Improve and expand existing entity extraction processes, incorporating new entities and models ...

Integral Federal, Inc.

Data Scientist

Mclean, VA · On-site

$90 - $120/hr

... Natural Language Processing (NLP) to analyze unstructured text and the integration of AI/ML platforms (e.g., AWS SageMaker, Azure Machine Learning) * Automate infrastructure and workflows using ...

Closure Technologies

Data Scientist

Chantilly, VA

Experience in working with artificial intelligence, machine learning, natural language processing, data mining, statistics, and algorithms * Ability to develop persistent monitoring applications for ...

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Internship Natural Language Processing information

What is an internship in natural language processing?

An Internship in Natural Language Processing (NLP) is a temporary position, often for students or recent graduates, where you gain hands-on experience working with technologies that enable computers to understand and generate human language. Interns in NLP typically assist with data collection, text analysis, model development, and research projects using machine learning and linguistic techniques. These internships help build foundational skills in programming, data science, and AI, and often require familiarity with languages like Python and libraries such as NLTK or spaCy. Through mentorship and real-world projects, interns learn about the latest advancements in NLP and build a portfolio that prepares them for future roles in AI and computational linguistics.

What types of projects can I expect to work on during a natural language processing internship?

As an NLP intern, you can expect to work on projects such as building and evaluating language models, developing text classification or sentiment analysis tools, or improving chatbots and search engines. You may also handle tasks like data preprocessing, annotation, and experimenting with state-of-the-art algorithms under the guidance of experienced researchers or engineers. Interns often collaborate closely with cross-functional teams, including data scientists, software engineers, and product managers, to deliver solutions that address real-world language challenges. This hands-on experience not only builds your technical skills but also provides insight into how NLP is applied in an industry setting.

What are the key skills and qualifications needed to thrive as an internship in natural language processing?

To thrive in a Natural Language Processing (NLP) internship, you generally need a solid background in computer science, mathematics, and linguistics, often supported by coursework or experience in machine learning and programming languages such as Python. Familiarity with NLP frameworks (like NLTK, spaCy, or Hugging Face), version control systems, and tools such as TensorFlow or PyTorch is typically expected. Strong analytical thinking, curiosity, and effective communication help interns stand out when tackling complex language challenges and collaborating with cross-functional teams. These skills are crucial for contributing to innovative NLP projects, understanding nuanced language data, and successfully adapting to evolving technical requirements.

What is the difference between Internship Natural Language Processing vs Data Analyst Intern?

AspectInternship Natural Language ProcessingData Analyst Intern
Required SkillsProgramming (Python), NLP libraries, basic ML conceptsExcel, SQL, data visualization tools
Work EnvironmentTech companies, research labs, AI startupsBusiness, finance, marketing sectors
Industry UsageAI, machine learning, NLP projectsData analysis, reporting, business insights
Common Search IntentLearning NLP, AI internshipsData analysis internships, business intelligence

Internship Natural Language Processing focuses on developing skills in NLP techniques, machine learning, and programming, often within tech or research environments. In contrast, Data Analyst Internships emphasize data manipulation, visualization, and reporting skills for business insights. Both roles require analytical skills but differ in technical focus and industry application.

What are the most commonly searched types of Natural Language Processing jobs in Virginia?

The most popular types of Natural Language Processing jobs in Virginia are:

What cities in Virginia are hiring for Internship Natural Language Processing jobs?

Cities in Virginia with the most Internship Natural Language Processing job openings:

Internship Natural Language Processing jobs near you

Applications Developer with Security Clearance

Level Up, LLC

Chantilly, VA • On-site

Contractor

Re-posted 20 days ago

Job description

This role will support applications development for a variety of tools and initiatives focused on streamlining operations, automating processes, and aligning customer solutions to the overarching digital architecture. The ideal candidate will help promote state-of-the-art IT solutions, collaborating with IT mission partners to share technology and lessons learned and ensure records management processes and requirements are included in the early design stages of IT solutions across the Intelligence Community. Additionally, this individual will work in concert with the customer technical interfaces to ensure future plans for technology are in line with the plans for the overall customer architecture. Demonstrated experience with:
• Building web applications in the Java Spring framework
• Working in Linux (Bash) shell scripting
• Development of applications in the Amazon Web Services cloud environment
• Extract, transform, and load (ETL) on large raw data sets
• Developing web-based platforms to perform searches or analytics on large data sets
• Design, develop, test and implement new applications based on project requirements Desired Skills:
Demonstrated experience with:
• Deployment of applications in the Amazon Web Services cloud environment
• Solr or ElasticSearch
• Proficiency in Python software development, especially web service development in Flask or Django
• Building web applications using the Angular 2+ framework
• Text analytics and its applications/role/use in business intelligence/business analytics (i.e. search, entity extraction, sentiment analysis, document summarization, document categorization)
• Researching and implementing machine learning algorithms for use in production systems
• Developing proof of concepts of new technologies and evaluating the state of the art in machine
• learning algorithms for text analytics
• Machine learning frameworks such as PyTorch, Keras, Tensorflow
• Data visualization tools (i.e. Tableau, Pandas, D3 s, ggplot, etc)
• In memory datastores (i.e. ElasticCache, Redis)
• NoSQL data stores such as MongoDB or DynamoDB
• MySQL or Postgres
• Natural Language Processing tools such as spaCy, NLTK, Stanford CoreNLP, or Gensim
• Natural Language Processing
• Optical character recognition (OCR) or image detection
• Developing solutions using opensource PDF libraries (Java, Python, or Javascript)

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