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Trainee Nlp Engineer Jobs (NOW HIRING)

Under this program, the postdoctoral trainee will be co-mentored by NU and JAX researchers working ... PhD in Computer Science, Engineering, Bioinformatics, Biomedical Data Science, or a related field

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Trainee Nlp Engineer information

What types of projects can a Trainee NLP Engineer expect to work on during their first year?

As a Trainee NLP Engineer, you will likely start by supporting senior team members on projects such as text classification, sentiment analysis, or chatbot development. Your responsibilities may include data preprocessing, annotating training datasets, implementing basic machine learning models, and evaluating model performance. You'll also collaborate closely with data scientists, software engineers, and sometimes domain experts to refine algorithms and integrate NLP solutions into larger systems. This hands-on experience helps you build foundational skills and prepares you for more complex tasks as you progress.

What are trainee NLP engineers?

Trainee NLP (Natural Language Processing) engineers are entry-level professionals who assist in designing, developing, and implementing systems that enable computers to understand and process human language. They typically work under the guidance of experienced engineers and data scientists, learning to apply techniques such as machine learning, text analysis, and language modeling. Their responsibilities often include data preprocessing, building and evaluating NLP models, and staying updated with advances in the field. This role is ideal for those interested in bridging computer science and linguistics, and it serves as a foundation for more advanced NLP engineering positions.

What are the key skills and qualifications needed to thrive as a Trainee NLP Engineer, and why are they important?

To thrive as a Trainee NLP Engineer, you need a solid understanding of programming (especially Python), machine learning fundamentals, and linguistic concepts, often backed by a degree in computer science or a related field. Familiarity with NLP libraries like NLTK, spaCy, or Hugging Face Transformers, as well as experience with software development tools and cloud platforms, is typically expected. Strong analytical thinking, problem-solving abilities, and effective communication skills help you work collaboratively and tackle complex language challenges. These competencies are vital for building, optimizing, and deploying NLP solutions that address real-world language processing tasks.

What is the difference between Trainee Nlp Engineer vs Junior Nlp Engineer?

AspectTrainee Nlp EngineerJunior Nlp Engineer
Required CredentialsTypically pursuing or recent graduate in Computer Science or related fieldBachelor's degree in relevant field, some practical experience
Work EnvironmentTraining programs, supervised projects, entry-level tasksIndependent task handling, project contributions
Employer & Industry UsageInternships, training programs in tech companies, research labsTech companies, AI startups, research institutions

The main difference between a Trainee Nlp Engineer and a Junior Nlp Engineer lies in experience and responsibility. Trainee roles focus on learning and training, often under supervision, while Junior roles involve applying skills more independently. Both positions are entry-level, but Junior Nlp Engineers typically have more practical experience and handle more complex tasks.

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Infographic showing various Trainee Nlp Engineer job openings in the United States as of May 2026, with employment types broken down into 28% Full Time, 13% Part Time, 1% Temporary, 54% Contract, and 4% Nights. Highlights an 96% Physical, 2% Hybrid, and 2% Remote job distribution.
Trainee Consultant-Data Science

Trainee Consultant-Data Science

Applexus Technologies

Seattle, WA • On-site

Full-time

Posted 28 days ago


Job description

United States of America Seattle Full Time
Applexus is a global technology and business consulting firm founded in 2005 and headquartered in Seattle, with delivery centers across North America, Canada, the United Kingdom, and India. We help enterprises realize value from AI and advanced analytics by applying AI/ML solutions directly to core business processes.
With strong foundations in SAP and enterprise platforms, Applexus delivers AI-driven transformation across SAP S/4HANA, data modernization, analytics, and cloud-native architectures. Our focus is on translating enterprise data into actionable intelligence that improves decision-making, operational efficiency, and business outcomes.
Applexus approaches AI pragmatically designing solutions that are scalable, governed, and ready for real-world enterprise deployment.
Applexus AI Practice
The Applexus AI Practice is built on deep domain expertise and a strong understanding of enterprise systems, particularly SAP. We combine this knowledge with our proprietary AI accelerators to help organizations move from AI exploration to production-ready implementation.
Our teams embed intelligent automation into the fabric of enterprise operations, enabling AI systems that operate within existing workflows rather than alongside them. These solutions are designed to integrate seamlessly with SAP landscapes while meeting enterprise standards for security, reliability, and performance.
A key area of focus is Agentic AI-autonomous, goal-driven systems that can reason and act across enterprise processes. By pairing agentic architectures with SAP domain expertise, Applexus delivers AI solutions that are context-aware, governed, and built for scale.
About the Role:
We are looking for a motivated and inquisitive Trainee Consultant - Data Science to join our team. In this role, you will contribute to real-world machine learning and data science projects under the mentorship of experienced professionals. This opportunity is ideal for individuals who are eager to apply their academic knowledge, expand their technical skills, and gain hands-on experience in AI/ML technologies in a collaborative environment.
Skills & Qualifications:
  • Master's degree in data science, Artificial Intelligence, or a related field from an accredited U.S. university.
  • Proficiency in Python
  • Familiarity with machine learning libraries and frameworks such as scikit-learn, TensorFlow, PyTorch, or Keras.
  • Solid understanding of statistics, linear algebra, and core machine learning algorithms.
  • Strong analytical and problem-solving abilities.
  • Capable of working both independently and collaboratively in a team environment.
Key Responsibilities:
  • Assist in the design, development, and evaluation of machine learning models.
  • Perform data cleaning, preprocessing, and feature engineering tasks.
  • Contribute to projects involving predictive modeling, natural language processing (NLP), or computer vision.
  • Utilize Python and tools such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch in project execution.
  • Collaborate with team members to analyze outcomes and generate actionable insights.
  • Maintain thorough documentation of work, models, and findings.
What You'll Gain:
  • Practical, hands-on experience with leading AI/ML technologies.
  • Mentorship and guidance from experienced professionals in the field.
  • Opportunity to contribute to real-world projects with measurable impact.
  • Potential consideration for future full-time roles will be based on performance during the training tenure.
How to Apply
Interested candidates may apply through the career site by submitting their full resume.
  • Preference will be given to U.S. Citizens and Green Card holders.
  • Candidates on OPT with STEM extension eligibility are also welcome to apply and will be considered based on merit. If on OPT, please specify the validity period and indicate STEM eligibility.

Location: Seattle, USA
Work Hours: Full Time (40 hours per week)
Join the Team