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Natural Language Processing Research Assistant Jobs in Alabama

LAUNCHTECH

Data Architect

Huntsville, AL · On-site

$160K - $210K/yr

... Research and Development for Enterprise Solutions (IRES) contract. What You'll Be Doing * Design ... Must have an understanding of Machine Learning (ML), Natural Language Processing (NLP), and ...

Launch Tech

Data Architect

Huntsville, AL · On-site

$62.75 - $80.75/hr

... Research and Development for Enterprise Solutions (IRES) contract. What You'll Be Doing * Design ... Must have an understanding of Machine Learning (ML), Natural Language Processing (NLP), and ...

Forhyre

Deep understanding of AI technologies, such as machine learning, natural language processing, and computer vision. * Strong knowledge of cloud computing platforms, such as AWS, Azure, or Google Cloud.

Guidehouse

Senior Palantir Foundry Engineer

Huntsville, AL

$103K - $141K/yr

... ML, natural language processing, knowledge graphs, semantic search, or advanced analytics solutions. * Experience supporting public health, healthcare, life sciences, biomedical research, or ...

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All JobsNatural Language Processing Research JobsNatural Language Processing Research Assistant JobsNatural Language Processing Research Assistant Jobs in Alabama

Natural Language Processing Research Assistant information

What does a natural language processing research assistant do?

A Natural Language Processing (NLP) Research Assistant supports research projects focused on enabling computers to understand, interpret, and generate human language. Their tasks often include collecting and preprocessing linguistic data, running experiments with machine learning models, and assisting in the analysis and interpretation of results. They may also contribute to writing research papers, literature reviews, and implementing prototype solutions. This role typically requires knowledge of programming, linguistics, and machine learning concepts.

What are the key skills and qualifications needed to thrive as a natural language processing research assistant, and why are they important?

To thrive as a Natural Language Processing (NLP) Research Assistant, you need a strong background in computer science, linguistics, and mathematics, often supported by a relevant degree or coursework. Familiarity with machine learning frameworks (such as TensorFlow or PyTorch), programming languages like Python, and NLP libraries (like NLTK or spaCy) is essential. Analytical thinking, attention to detail, and effective communication are important soft skills in this role. These skills enable you to contribute to cutting-edge language models and research projects, ensuring accuracy and innovation in NLP solutions.

What are some typical challenges faced by a natural language processing research assistant when working with large datasets?

As a Natural Language Processing (NLP) Research Assistant, you may encounter challenges such as cleaning and preprocessing vast amounts of unstructured text, dealing with noisy or imbalanced data, and ensuring data privacy. Handling computational limitations and optimizing models for efficiency are also common hurdles, especially when training deep learning models on large corpora. Collaborating closely with data engineers and senior researchers is essential to overcome these obstacles and to ensure that data pipelines and experimental results are robust and reproducible.

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

AspectNatural Language Processing Research AssistantData Scientist
Required CredentialsTypically a master's or PhD in computer science, linguistics, or related fieldsOften a bachelor's or master's in data science, statistics, or related areas; advanced degrees preferred
Work EnvironmentAcademic or research labs, tech companies focusing on NLP projectsBusiness, tech companies, or consulting firms analyzing large datasets
Employer & Industry UsageResearch institutions, universities, AI companiesTech firms, finance, healthcare, marketing

While both roles involve data analysis and programming, Natural Language Processing Research Assistants focus on developing NLP models and conducting research, often in academic settings. Data Scientists analyze diverse datasets to derive insights and support business decisions. The roles overlap in technical skills but differ in their primary objectives and work environments.

Infographic showing various Natural Language Processing Research Assistant job openings in Alabama as of August 2026, with employment types broken down into 46% Full Time, 27% Part Time, and 27% Contract. Highlights an 100% In-person job distribution.

Generative AI Automation Engineer - Remote Job

Huntsville, AL • Remote

EnthuZiastic
E-Learning • 11 - 50 employees
Learn more about EnthuZiasticexternal

Full-time

Re-posted 22 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