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Internship Natural Language Processing Jobs in Minnesota

THOMSON REUTERS

Senior Research Engineer

Eagan, MN · Hybrid

$106K - $146K/yr

Exposure to Natural Language Processing (NLP) problems and familiarity with key tasks such as Named Entity Recognition (NER), Information Extraction, Information Retrieval, Text classification ...

Mayo Clinic

Data Analyst

Rochester, MN · On-site

Applies machine learning, natural language processing, and programmatic analytics (e.g., Python, SQL, and R) to generate automated, actionable insights. Partners with AI/ML, engineering, and business ...

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Internship Natural Language Processing information

What types of projects can I expect to work on during a Natural Language Processing (NLP) 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 Natural Language Processing, and why are they important?

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 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 are the most commonly searched types of Natural Language Processing jobs in Minnesota? The most popular types of Natural Language Processing jobs in Minnesota are:
What cities in Minnesota are hiring for Internship Natural Language Processing jobs? Cities in Minnesota with the most Internship Natural Language Processing job openings:
Internship Natural Language Processing jobs near you
Generative AI Automation Engineer - Remote Job

Generative AI Automation Engineer - Remote Job

EnthuZiastic

Plymouth, MN • On-site

Other

Posted 3 days ago

Job description

About Us

Our mission is to bring people together and connect them into a community to nurture each other. We aim to share a conducive environment, a joyous space to grow and excel; a world brimming with selfless love and enough kindness. We strive to enrich each of our lives with kaleidoscopic memories we make here - vibrant, lively, of all hues and colors.

Job Description

​

This is a remote position.

We are seeking a highly skilled and innovative Generative AI Automation Engineer to join our team. The ideal candidate will be responsible for designing, developing, and implementing automation solutions powered by Generative AI models. This role requires a combination of expertise in machine learning, natural language processing, software engineering, and automation frameworks to drive efficiency and innovation in business processes.

Key Responsibilities:

Generative AI Model Implementation:

  • Develop, fine-tune, and deploy Generative AI models (e.g., GPT, Stable Diffusion, DALL-E, etc.) for automation tasks.

  • Integrate pre-trained models or build custom models for specific use cases.

Automation Design and Development:

  • Design and implement AI-driven workflows and solutions to automate repetitive tasks and improve process efficiency.

  • Develop APIs, scripts, and tools for seamless integration of AI models into existing systems.

Data Management:

  • Collect, preprocess, and analyze large datasets for training and validating AI models.

  • Ensure data privacy and compliance with regulatory requirements during data handling.

System Integration:

  • Collaborate with software development and IT teams to integrate Generative AI solutions with enterprise systems.

  • Build and maintain pipelines for real-time AI inference and automation.

Monitoring and Optimization:

  • Continuously monitor AI automation solutions to ensure accuracy, efficiency, and reliability.

  • Optimize models and processes based on performance metrics and user feedback.

Research and Innovation:

  • Stay updated with the latest advancements in Generative AI and automation technologies.

  • Identify opportunities for implementing cutting-edge AI solutions to address business challenges.

Documentation and Collaboration:

  • Document technical designs, workflows, and implementation strategies.

  • Collaborate with cross-functional teams, including product managers, data scientists, and software engineers.

Requirements

Required Qualifications:

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

  • Strong programming skills in Python, with experience in frameworks like TensorFlow, PyTorch, or Hugging Face.

  • Proficiency in designing and deploying machine learning models, particularly in Generative AI.

  • Experience with automation tools (e.g., RPA, workflow orchestration tools).

  • Familiarity with cloud platforms (AWS, Azure, or Google Cloud) and containerization technologies (Docker, Kubernetes).

  • Solid understanding of data structures, algorithms, and software design principles.

  • Strong analytical and problem-solving skills.

  • Excellent communication and teamwork abilities.

Preferred Qualifications:

  • Experience with NLP, image generation, or multimodal AI models.

  • Hands-on experience with APIs for AI services like OpenAI, Cohere, or Google AI.

  • Familiarity with prompt engineering and fine-tuning Generative AI models.

  • Knowledge of MLOps practices for deploying and maintaining AI solutions.

  • Previous experience in automation or workflow optimization projects.

Benefits

Why Join Us?

  • Work with cutting-edge Generative AI technologies.

  • Collaborate with a team of forward-thinking innovators.

  • Make a tangible impact on the future of automation and AI-driven processes.

If you are passionate about leveraging Generative AI to create innovative automation solutions, we invite you to apply and be a part of our dynamic and growing team.

Apply