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Entry Level Nlp Research Scientist Jobs (NOW HIRING)

Point72

Quantitative Research Intern (NLP)

New York, NY · On-site

The ideal candidate will have strong machine learning, data science and software engineering skills ... Using NLP to construct features from varied datasets * Formulating research hypotheses to derive ...

Core4ce Careers

Materials Research Scientist

Dayton, OH · On-site

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

Core4ce is seeking an entry-level Ph.D. scientist to support an advanced materials research and development program spanning single-crystal growth, coating deposition, and solid-state materials ...

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Entry Level Nlp Research Scientist information

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$50.5K

$130.1K

$174K

How much do entry level nlp research scientist jobs pay per year?

As of Aug 19, 2026, the average yearly pay for entry level nlp research scientist in the United States is $130,117.00, according to ZipRecruiter salary data. Most workers in this role earn between $107,500.00 and $173,000.00 per year, depending on experience, location, and employer.

What does an entry level NLP research scientist do?

An Entry Level NLP (Natural Language Processing) Research Scientist works on developing and improving algorithms that allow computers to understand, interpret, and generate human language. They typically assist with data collection, preprocessing, model training, and evaluation under the guidance of senior researchers. Tasks may include literature reviews, experimental design, and contributing to research papers or technical documentation. Their work helps advance technologies like chatbots, voice assistants, and machine translation systems.

What are the key skills and qualifications needed to thrive as an entry level NLP research scientist?

To thrive as an Entry Level NLP Research Scientist, you need a strong background in computer science, mathematics, and linguistics, typically supported by a relevant degree (such as in Computer Science or Computational Linguistics). Familiarity with programming languages like Python, machine learning frameworks (e.g., TensorFlow, PyTorch), and NLP libraries (such as spaCy or NLTK) is essential. Strong analytical thinking, creativity, and effective communication skills help you collaborate and innovate in research settings. These competencies enable you to design, implement, and evaluate NLP models that advance language technologies.

What are some common challenges faced by entry level NLP research scientists when transitioning from academia to industry?

Entry-level NLP research scientists often find the transition from academia to industry challenging due to differences in project timelines, expectations, and collaboration styles. While academic research emphasizes novelty and long-term investigations, industry projects typically prioritize practical impact and faster iteration cycles. Adjusting to working in cross-functional teams with engineers, product managers, and stakeholders can require effective communication and adaptability. Additionally, managing real-world data constraints and scalability issues is crucial in industry settings. Embracing these changes and being open to learning from colleagues with diverse backgrounds will help ease the transition and contribute to professional growth.

What is the difference between Entry Level Nlp Research Scientist vs Data Scientist?

AspectEntry Level Nlp Research ScientistData Scientist
Required CredentialsBachelor's or Master's in Computer Science, NLP, or related field; knowledge of NLP toolsBachelor's or Master's in Data Science, Statistics, or related field; programming skills
Work EnvironmentResearch-focused, academic or R&D labs, tech companiesBusiness analytics, data analysis, product development teams
Industry UsageAI research, NLP product developmentBusiness intelligence, marketing, finance, tech

Entry Level Nlp Research Scientists focus on developing and improving NLP algorithms, often in research or R&D settings. Data Scientists analyze data to inform business decisions across various industries. While both roles require programming skills and a background in data or language processing, Nlp Research Scientists are more research-oriented, whereas Data Scientists focus on applying data analysis to solve business problems.

What are the most commonly searched types of Nlp Research Scientist jobs?

The most popular types of Nlp Research Scientist jobs are:

What states have the most Entry Level Nlp Research Scientist jobs?

States with the most job openings for Entry Level Nlp Research Scientist jobs include:

Entry Level Nlp Research Scientist jobs near you
Infographic showing various Entry Level Nlp Research Scientist job openings in the United States as of June 2026, with employment types broken down into 66% Full Time, 17% Contract, and 17% Nights. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $130,117 per year, or $62.6 per hour.

Research Scientist - Data

Institute of Foundation Models

Sunnyvale, CA • On-site

$150K - $450K/yr

Full-time

Re-posted 6 days ago

Job description

About the Institute of Foundation Models
We are a dedicated research lab for building, understanding, using, and risk-managing foundation models. Our mandate is to advance research, nurture the next generation of AI builders, and drive transformative contributions to a knowledge-driven economy.

As part of our team, you’ll have the opportunity to work on the core of cutting-edge foundation model training, alongside world-class researchers, data scientists, and engineers, tackling the most fundamental and impactful challenges in AI development. You will participate in the development of groundbreaking AI solutions that have the potential to reshape entire industries. Strategic and innovative problem-solving skills will be instrumental in establishing MBZUAI as a global hub for high-performance computing in deep learning, driving impactful discoveries that inspire the next generation of AI pioneers.



The Role
 
As a Research Scientist in the Data team, your primary responsibility is to curate high quality data at the web-scale to fuel the development of next generation foundation models. You will work on exploring andconsolidatingdata sources and collaborate with cross-functional teams to conduct in-depth data research, contributing to MBZUAI’s mission of driving impactful AI discoveries and positioning the institution as a leader in the global AI research community. Your expertise will be key in enhancing the performance of large-scale machine learning models, while supporting the development of transformative AI tools that can influence industries worldwide. 
Key Responsibilities
  • Pioneer web-scale data collection and curation methodologies for LLMs and multi-modal foundation models. 
  • Design and implement novel data synthesis pipelines for code, mathematics, and agentic reasoning datasets. 
  • Trace the impact of data from pre-training to final model capabilities and create automated quality assessment frameworks for massive datasets 
  • Design data recipes that maximize model capabilities across diverse domains. 
  • Optimize data-model co-design for improved training dynamics. 
  • Contribute to research papers and represent MBZUAI at industry conferences and events, showcasing the institution’s AI research and innovation. 
Academic Qualifications
  • Minimum: Master’s in Computer Science, Data Science, or a related technical field, or equivalent practical experience required. 
  • Preferred: PhD or equivalent research experience in Machine Learning, NLP, or Data Science with a focus on LLMs and data is preferred. 
Professional Experience
  • Experience working with large language models, including evaluation, fine-tuning, and prompt engineering. 
  • Strong Python development skills with a focus on research-grade code and scalable data pipelines. 
  • Familiarity with collecting and processing large-scale datasets from open-source and web resources. 
  • Demonstrated ability to work with ML infrastructure (e.g., model evaluation, optimization, debugging). 
  • Proactive mindset with the ability to identify impactful research questions and execute on them with minimal supervision. 
  • Effective communication and collaboration skills for working in cross-functional teams. 
Preferred   
  • Prior research experience in areas such as web data curation and mixing, synthetizing complex datasets for training, LLM evaluation, post-training data, efficient inference, LLM-as-a-judge, tokenization. 
  • Strong publication record in leading AI conferences (e.g., NeurIPS, ICLR, ICML, EMNLP) and/or prior contributions to open-source AI research or data tools. 
  • Hands-on experience training language/mutli-modal models from scratch. 
Visa Sponsorship
This position is eligible for visa sponsorship.

Benefits Include
*Comprehensive medical, dental, and vision benefits 
 *Bonus
*401K Plan
*Generous paid time off, sick leave and holidays
*Paid Parental Leave
*Employee Assistance Program
*Life insurance and disability