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Natural Language Processing Research Jobs (NOW HIRING)

Cypress HCM

LLM Research Engineer

Mountain View, CA

$90 - $121.86/hr

Conduct research on cutting-edge techniques in natural language processing (NLP) and machine learning to improve model performance. * Explore advancements in transformer architectures, multi-modal ...

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What are the key skills and qualifications needed to thrive as a Natural Language Processing (NLP) Researcher, and why are they important?

To thrive as a Natural Language Processing Researcher, you need a solid background in computer science, machine learning, linguistics, and typically a graduate degree in a relevant field. Proficiency with programming languages like Python, deep learning frameworks (such as TensorFlow or PyTorch), and NLP libraries (like NLTK or spaCy) is essential, along with experience in publishing academic research. Strong analytical thinking, creativity, and effective communication skills help in developing novel solutions and collaborating within interdisciplinary teams. These skills are vital for advancing the field, solving complex language problems, and driving impactful research outcomes.

What are some typical challenges faced by professionals in Natural Language Processing (NLP) research roles?

NLP researchers often encounter challenges related to the complexity and ambiguity of human language, such as handling sarcasm, idioms, or multilingual datasets. Keeping up with rapid advancements in deep learning architectures and large language models is also a common demand. Additionally, working with large-scale datasets requires robust data cleaning and preprocessing skills, as well as collaboration with cross-functional teams like data engineers and product managers to ensure research findings translate into practical applications.

What is Natural Language Processing (NLP) research?

Natural Language Processing (NLP) research focuses on enabling computers to understand, interpret, and generate human language. Researchers in this field work on developing algorithms and models that help machines process text and speech, such as chatbots, translation systems, and sentiment analysis tools. NLP research combines knowledge from linguistics, computer science, and artificial intelligence to solve complex language-related problems. Common tasks include language modeling, machine translation, and information extraction.

What is the difference between Natural Language Processing Research vs Data Scientist?

AspectNatural Language Processing ResearchData Scientist
Required CredentialsAdvanced degrees in CS, NLP, or AI; research experienceDegree in CS, Statistics, or related; some research experience beneficial
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, tech companies, analytics teams
Employer & Industry UsageUniversities, research institutions, tech companies focusing on NLPVarious industries including finance, healthcare, tech, e-commerce
Common Search & Comparison IntentUnderstanding research roles in NLPUnderstanding data analysis and modeling roles

Natural Language Processing Research focuses on developing new algorithms and models to advance NLP technology, often within academic or research settings. Data Scientists analyze data to extract insights, build predictive models, and support business decisions. While both roles require strong analytical skills, NLP Research emphasizes innovation in language models, whereas Data Scientists focus on applying data techniques across various domains.

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Infographic showing various Natural Language Processing Research job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, and 15% Part Time. Highlights an 93% Physical, and 7% Remote job distribution.
Artificial Intelligence & Natural Language Processing Research Scientist

Artificial Intelligence & Natural Language Processing Research Scientist

Howard University

Washington, DC • On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired today. Applications are no longer accepted.

Howard University rating

8.7

Company rating: 8.7 out of 10

Based on 7 frontline employees who took The Breakroom Quiz

38th of 529 rated colleges and universities

Job description

The Talent Acquisition department hires qualified candidates to fill positions which contribute to the overall strategic success of Howard University. Hiring staff "for fit" makes significant contributions to Howard University's overall mission.
At Howard University, we prioritize well-being and professional growth.
Here is what we offer:

  • Health & Wellness: Comprehensive medical, dental, and vision insurance, plus mental health support
  • Work-Life Balance: PTO, paid holidays, flexible work arrangements
  • Financial Wellness: Competitive salary, 403(b) with company match
  • Professional Development: Ongoing training, tuition reimbursement, and career advancement paths
  • Additional Perks: Wellness programs, commuter benefits, and a vibrant company culture
Join Howard University and thrive with us!
https://hr.howard.edu/benefits-wellness
JOB PURPOSE:
Employee will spearhead innovative projects, mentor emerging talent, and push the boundaries of technology in areas such as natural language processing and artificial intelligence.
SUPERVISORY AUTHORITY:
None
NATURE AND SCOPE:
Internal contacts include RITA HQ Team and the entire Howard University community. External contacts include as directed.
PRINCIPAL ACCOUNTABILITIES:
  • Lead AI research initiatives from conception to implementation.
  • Develop cutting-edge AI systems, tailoring solutions to complex research queries.
  • Analyze research data critically, translating findings into actionable insights.
  • Collaborate across disciplines, integrating diverse expertise into your work.
  • Disseminate knowledge through scholarly papers and compelling presentations to stakeholders.
  • Remain at the forefront of AI/NLP advancements, integrating new technologies and methodologies.
  • Design and validate NLP techniques, contributing to the broader field with innovative solutions.
  • Engage in developing and evaluating human-machine interfaces and systems integration, enhancing human performance through technology.
CORE COMPETENCIES:
  • Mastery of programming languages (Python, Java, C++, C, R) and command-line scripting.
  • Expertise in ML frameworks (scikit-learn, TensorFlow, PyTorch) and data processing (JSON, XML).
  • Exceptional project management, communication, and collaborative skills.
  • Experience in high-performance computing, secure network AI development, and simulation tools.
  • Proficiency in UI/UX development.

MINIMUM REQUIREMENTS:
Bachelor's Degree or higher in Computer Engineering/Science, Engineering, or IT; equivalent experience considered. 5+ years in machine learning and data science; advanced degrees may offset experience requirements. An advanced degree (Postgraduate or Ph.D.) in a relevant field is preferred. A history of designing algorithms in AI/NLP or related fields. Willing and able to travel and obtain/maintain a US Top Secret/SCI level security clearance. U.S. citizenship is required due to federal export control and security compliance requirements.
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