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Nltk Jobs (NOW HIRING)

Multivision Inc-IL

AI Engineer Python

Chicago, IL

... Keras, NLTK, or spaCy Familiarity and experience with Databases like Postgres, Redshift, MSSQL Soft Skills: Proven ability to deliver timely results in professional work environments. Strong ...

Elite WorkForce Inc

PA · On-site

Proficiency in NLP tools (e.g., spaCy, Hugging Face, NLTK). * Hands-on experience with Microsoft Dynamics Contact Center solution and Azure AI services. * Experience with cloud platforms (Azure) and ...

Suncap Technology

Required Skills

Austin, TX

... NLTK, Gensim · Interested in Text analytics, Natural Language processing, Classification and Clustering · Significant experience creating clean, insightful dashboards for executives and non ...

Marencor

Data Scientist with Python

Dallas, TX · On-site

Portfolio of LLM applications and sample projects * 2+ years of NLP experience using tools such as NLTK, SpaCy, and Beautiful Soup * 1+ years of LLM experience building RAG systems at scale (10,000 ...

Software People, Inc.

AI Developer

Lansing, MI · On-site

Skills Needed • 3+years in TensorFlow, PyTorch, Keras, or Scikit-learn. • 3+ years in microservices. • 3+years in SpaCy, NLTK, or Hugging Face's • 3+years in Tesseract, Google Vision API, or ...

Bazze

AI Engineer

San Francisco, CA · On-site

... NLTK, Spacy, or Hugging Face's Transformers. Company : Bazze provides an alternative data marketplace that analyzes and assesses risks posed by hostile foreign actors. Founded in 2018, the company is ...

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How much do nltk jobs pay per hour?

As of May 30, 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
What job categories do people searching Nltk jobs look for? The top searched job categories for Nltk jobs are:
Nltk jobs near you
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.

Data scientist with Python and AI/ML consultant.

Accord Technologies Inc.

Alpharetta, GA • On-site

Contractor

Posted 26 days ago

Job description

Title: Data Scientist with Python and AI/ML consultant.
Location: Alpharetta, GA (100% onsite)
Inperson interview required
Position type; W2 contract

We are looking for a talented Data Scientist with Python and AI/ML expertise to build predictive models, deploy machine learning solutions, and deliver advanced analytics across enterprise platforms. The role focuses on transforming data into actionable business insights using modern AI techniques.

Key Responsibilities

  • Develop and deploy machine learning models using Python.

  • Perform data exploration, feature engineering, and model evaluation.

  • Build AI/ML solutions for prediction, classification, NLP, and recommendation systems.

  • Work with large datasets using SQL, Pandas, NumPy, Spark.

  • Implement deep learning models using TensorFlow / PyTorch.

  • Develop NLP pipelines using spaCy, NLTK, HuggingFace.

  • Collaborate with product and engineering teams to operationalize models (MLOps).

  • Monitor model performance and retrain as required.

  • Create dashboards and presentations for stakeholders.

  • Support experimentation and A/B testing frameworks.

Required Skills

  • Strong proficiency in Python for data science and ML.

  • Experience with Scikit-learn, TensorFlow, PyTorch.

  • Strong knowledge of statistics, probability, and linear algebra.

  • Experience with SQL and big data tools (Spark, Hadoop).

  • Hands-on experience with NLP, computer vision, or recommendation systems.

  • Knowledge of MLOps, CI/CD for ML models.

  • Experience deploying models in cloud environments (AWS/Azure/GCP).