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Internship Natural Language Processing Intern Jobs in Baltimore, MD

Centurion Consulting Group

Sr Data Scientist

Woodlawn, MD · On-site

$125K - $195K/yr

Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction concepts including Named Entity Recognition, Blocking and Indexing, String Distance ...

Dcode Talent LLC

GenAI Engineer

Woodlawn, MD · On-site

Machine Learning, Deep Learning, Neural Networks, Python, Natural Language Processing, Prompt Engineering, and Data Management and Preprocessing. Position Description: · Design and develop ...

Omm IT Solutions

Senior Data Scientist

Woodlawn, MD · On-site

Strong practical experience with Natural Language Processing (NLP), Text Processing, and Information Extraction concepts including Named Entity Recognition, Blocking and Indexing, String Distance ...

AIToolboard

AI Research Scientist

Baltimore, MD · On-site

$150 - $200/hr

... deep learning, natural language processing, computer vision, or reinforcement learning ... Mentor junior researchers and interns. Present research findings to technical and non-technical ...

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Internship Natural Language Processing Intern information

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$9

$17

$23

How much do internship natural language processing intern jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for internship natural language processing intern in Baltimore, MD is $17.20, according to ZipRecruiter salary data. Most workers in this role earn between $14.33 and $19.09 per hour, depending on experience, location, and employer.

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

AspectInternship Natural Language Processing InternData Science Intern
Required CredentialsRelevant coursework in NLP, computer science, or linguistics; basic programming skillsBackground in statistics, mathematics, or computer science; programming skills
Work EnvironmentResearch-focused, often in AI or NLP teams within tech companies or research labsData analysis, modeling, and visualization tasks in tech, finance, or consulting firms
Employer & Industry UsageCommon in AI startups, tech giants, and research institutionsWidely used across tech, finance, healthcare, and consulting industries

Both roles are internship positions requiring programming skills and relevant coursework. NLP Interns focus specifically on language processing tasks, while Data Science Interns work on broader data analysis and modeling projects. The choice depends on your interest in language technologies versus general data analysis.

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Software Engineer (Language Modeling), BS+12 yrs

Link, LLC

Columbia, MD • On-site

Full-time

Re-posted 20 days ago

Job description

Description: We are seeking a highly skilled and motivated Sr. LLM Engineer to join our team in driving the advancement of our Language Model infrastructure. As a key member of our AI/ML team, you will be responsible for the training, hosting, and optimization of Large Language Model (LLM) instances within our compute environment. The ideal candidate should possess a strong passion for pushing the boundaries of language technology, a deep understanding of LLM architectures, and the grit to tackle complex challenges head-on. This role requires a self-reliant individual with a drive to identify and fix inefficiencies, constantly striving to improve the codebase and optimize model performance. If you thrive in a fast-paced environment and have an unwavering commitment to delivering cutting-edge language solutions, this position is for you.
Responsibilities:
• Design, develop, and maintain the infrastructure for training, hosting, and serving LLM instances.
• Optimize model training pipelines to achieve high performance and resource efficiency.
• Implement and integrate state-of-the-art LLM architectures and techniques.
• Collaborate with cross-functional teams to understand business requirements and deliver impactful language solutions.
• Monitor and analyze model performance metrics, identifying areas for improvement and implementing optimizations.
• Develop and maintain documentation, best practices, and coding standards for LLM development and deployment.
• Stay up-to-date with the latest advancements in LLM research and industry trends, and incorporate them into our projects.
• Mentor and guide junior engineers, fostering a culture of continuous learning and knowledge sharing.
Skills Requirements:
• 12+ years of experience in software engineering, with a focus on machine learning or natural language processing.
• Degree in Computer Science, Artificial Intelligence, or a related field.
• Strong expertise in deep learning frameworks such as TensorFlow, PyTorch, or MXNet.
• Proficiency in programming languages such as Python, C++, or Java.
• Solid understanding of LLM architectures, training techniques, and evaluation methodologies.
• Familiarity with cloud platforms (e.g., AWS, GCP) and their machine learning services.
• Knowledge of software engineering best practices, including version control, testing, and continuous integration/deployment.
• Excellent problem-solving and debugging skills.
• Strong communication and collaboration abilities to work effectively with cross-functional teams.
Nice to Haves:
• Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, or a related field.
• Proven track record of implementing and deploying large-scale LLM systems in production environments.
• Experience with distributed computing frameworks like Apache Spark or Hadoop.
• Experience with natural language understanding, generation, and dialogue systems.
• Familiarity with techniques such as transfer learning, few-shot learning, and reinforcement learning.
• Contributions to open-source projects or research publications in the field of LLMs.
• Experience with serving models using APIs and building scalable inference pipelines.
• Knowledge of DevOps practices and tools like Docker, Kubernetes, and Jenkins.
YOE Requirement: 12 yrs., B.S. in a technical discipline or 4 additional yrs. in place of B.S.
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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