1

Nltk Jobs (NOW HIRING)

... NLTK, Apache OpenNLP, or other natural language software packages for Parts of Speech tagging, ambiguity resolution, and syntactic parsing. • Master's or PhD degree in linguistics or computational ...

Agent Engineer

San Francisco, CA · On-site

$17.75 - $23.50/hr

Familiarity with natural language processing techniques and libraries (e.g., NLTK, spaCy) * Knowledge of reinforcement learning and decision-making algorithms * Strong problem-solving skills and ...

Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark). * Knowledge of machine learning techniques (i.e. classification, regression, and clustering). * Understand machine learning ...

Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark). * Knowledge of machine learning techniques (i.e. classification, regression, and clustering). * Understand machine learning ...

Python, Scikit, NLTK, Numpy, Pandas, TensorFlow, Keras, R, Spark). * Basic knowledge of machine learning techniques (i.e. classification, regression, and clustering). * Understand machine learning ...

Experience with NLP frameworks: spaCy, NLTK, BERT, GPT-based models. * Strong experience in using Neo4J, Mongo DB * Experience in developing and deploying conversational AI solutions, preferably in ...

next page

Showing results 1-20

Nltk information

See salary details

$18

$52

$80

How much do nltk jobs pay per hour?

As of May 29, 2026, the average hourly pay for nltk in the United States is $52.51, according to ZipRecruiter salary data. Most workers in this role earn between $21.88 and $69.71 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as an NLP Engineer using NLTK, and why are they important?

To thrive as an NLP Engineer using NLTK, you need a solid background in computer science, strong programming skills in Python, and a good understanding of linguistics and natural language processing concepts. Familiarity with NLTK, other NLP libraries (like spaCy), and experience with machine learning frameworks and data processing tools are typically required. Strong analytical thinking, attention to detail, and effective communication skills help you develop robust language models and collaborate with interdisciplinary teams. These skills are crucial for building accurate, efficient, and innovative NLP solutions that meet user and business needs.

What are the typical challenges faced by professionals working with NLTK in natural language processing projects?

Professionals using NLTK for natural language processing often encounter challenges such as handling large datasets efficiently, ensuring compatibility with diverse text formats, and integrating NLTK with other machine learning libraries. Additionally, because NLTK is primarily used for research and prototyping, deploying production-ready solutions may require additional effort in optimizing performance and scalability. Collaborating with data engineers and software developers is common to address these challenges and deliver robust NLP applications.

What is NLTK and what is it used for?

NLTK, or Natural Language Toolkit, is a Python library used for working with human language data (text). It provides easy-to-use interfaces to over 50 corpora and lexical resources, along with various text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning. NLTK is widely used in research and teaching for natural language processing (NLP) tasks, making it a popular choice for prototyping and building text analysis applications. It's particularly valued for its comprehensive documentation and active community support.

What is the difference between Nltk vs Text Analyst?

AspectNltkText Analyst
Required CredentialsKnowledge of Python, basic programming skillsDegree in linguistics, data analysis, or related field
Work EnvironmentProgramming, data processing, research projectsData interpretation, report writing, client interaction
Industry UsageNatural language processing, AI, machine learningMarket research, media analysis, content evaluation

While Nltk is a Python library used for natural language processing tasks, a Text Analyst applies various tools, including Nltk, to interpret and analyze textual data. Nltk provides the technical foundation, whereas a Text Analyst focuses on deriving insights from data using such tools.

More about Nltk jobs
Infographic showing various Nltk job openings in the United States as of May 2026, with employment types broken down into 80% Full Time, 1% Part Time, and 19% Contract. Highlights an 76% Physical, 4% Hybrid, and 20% Remote job distribution, with an average salary of $109,227 per year, or $52.5 per hour.
Senior NLP Scientist/Engineer

Senior NLP Scientist/Engineer

Brilent

San Mateo, CA • On-site

Full-time

Medical, Dental

Posted 15 days ago


Job description

Company Description
Brilent is a data science tech company developing a SaaS solution to help recruiters quickly and effectively identify the right talent to hire. The Brilent team brings together deep experience in machine learning, and data science from leading edge companies to solve the growing problem of leveraging big data to effectively identify and connect with the right talent. With the Brilent solution, pre-screening candidates take minutes as opposed to hours or days thus shortening the time-to-hire, and increasing the number of candidate placements.
WHY US?
Brilent is a well-funded, award winning startup located in the Silicon Valley. We are building the next-generation, big data talent platform that aims to revolutionize the hiring ecosystem around the world. Our team consists of machine learning and data science experts and recruiting veterans from leading edge companies such as Facebook, Microsoft and HP, and graduates of top-tier universities (University of Waterloo, CMU, University of Michigan, USC, etc.). We are looking for exceptional people to scale our business and build innovative products. Come join the revolution!
Job Description
Responsibilities
• Develop document/text parsing technologies and build them into Brilent's core recommendation engine
• Implement, evaluate and deploy advanced parsing and matching algorithms
• Work with backend engineers, and UI/UX designers and engineers to define product roadmap and feature specifications
• Stay current with the latest technological advances in text mining, NLP processing, and machine learning
Qualifications
• Extensive experiences in NLP processing including POS tagging, syntactic/semantic analysis, ambiguity resolution, named entity recognition, relation extraction, text classification, and discourse analysis
• Working knowledge and hands-on experience of parsing entities and their relations from text documents/corpus
• Strong machine learning background and experience of using ML techniques in NLP applications
• Strong programming skills in Java/C/C++/Python
• Proficient with relational database (e.g., MySQL) and knowledgeable in non-relational or graph databases
• Familiar with open-source or commercial text processing and/or NLP tools, such as Apache Lucene or Solr, Stanford CoreNLP, NLTK, Apache OpenNLP, or other natural language software packages for Parts of Speech tagging, ambiguity resolution, and syntactic parsing.
• Master's or PhD degree in linguistics or computational linguistics, or related degree in machine learning or Computer science
Additional Information
We offer competitive salaries, stock options, and full benefits, including health and dental coverage, all meals included, snacks, travel reimbursement, etc.