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Spacy Jobs (NOW HIRING)

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Hands-on Python experience using pandas, NumPy, scikit-learn, matplotlib, spaCy, Keras, or similar libraries. * R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages. * SQL ...

Python Developer

Dallas, TX · On-site

$49.75 - $68.50/hr

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 ...

Junior Data Scientist

Arlington, VA · On-site

$100K - $120K/yr

Hands-on Python experience using pandas, NumPy, scikit-learn, matplotlib, spaCy, Keras, or similar libraries. * R experience using tidyverse, tidymodels, ggplot2, Shiny, or equivalent packages. * SQL ...

Engineer II Premium

Phoenix, AZ

$82K - $110K/yr

... NLTK, spaCy), pandas, Matplotlib - Vector databases (ChromaDB, FAISS, pgvector) - Cloud Deployment (AWS/GCP/Azure) - Docker - Git - AI/ML Skills: - Retrieval-Augmented Generation (RAG) - Prompt ...

Java Developer with Instabase

Columbus, OH · On-site

$49.25 - $63.75/hr

Advise and instruct on the ecosystem of open source tools python spacy pandas sklearn etc compatible with Instabase and how customers can use them Skills Mandatory Skills : Instabase Java,HTML/HTML5 ...

For language-based AI, expertise in NLP techniques and libraries such as NLTK, spaCy, and Hugging Face Transformers is key. * Cloud Computing and MLOps: Knowledge of cloud platforms (AWS, GCP, Azure ...

Requirements Proficiency in Python and NLP frameworks (Hugging Face, spaCy, PyTorch, TensorFlow). Strong understanding of transformer architectures and generative models like GPT or BERT. Experience ...

Required : • Proficiency in Python and ML libraries (TensorFlow, PyTorch, Hugging Face, SpaCy, etc.) • Experience with OCR tools (e.g., Tesseract, AWS Textract, Google Vision) • Strong ...

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Spacy information

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How much do spacy jobs pay per year?

As of Jul 21, 2026, the average yearly pay for spacy in the United States is $141,976.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,500.00 and $163,500.00 per year, depending on experience, location, and employer.

What are some common challenges faced by professionals working with spaCy in natural language processing projects?

Professionals using spaCy often encounter challenges such as customizing pre-trained models to fit domain-specific language, handling large-scale text data efficiently, and integrating spaCy pipelines with other machine learning frameworks. Additionally, staying updated with frequent library updates and best practices can be demanding. Collaboration with data scientists and software engineers is typically necessary to ensure seamless deployment and scaling of NLP solutions in production environments.

What are the key skills and qualifications needed to thrive as a Natural Language Processing (NLP) Engineer specializing in spaCy, and why are they important?

To thrive as an NLP Engineer specializing in spaCy, you need a solid background in computer science, linguistics, and machine learning, often supported by a relevant degree. Proficiency with Python programming, the spaCy library, and experience with tools like Jupyter Notebooks and version control systems are typically required. Strong analytical thinking, problem-solving skills, and effective communication help you design and implement robust language models and collaborate with multidisciplinary teams. These skills and qualities are crucial for developing, optimizing, and deploying high-quality NLP solutions that meet real-world business needs.

What is a Spacy job or role?

A Spacy job typically refers to a professional who works with spaCy, an open-source natural language processing (NLP) library in Python. These roles often involve developing, implementing, or maintaining NLP applications such as text classification, named entity recognition, or information extraction using spaCy. Professionals in this field may work as data scientists, NLP engineers, or machine learning specialists, leveraging spaCy's efficient and easy-to-use tools to process and analyze large volumes of text data. Familiarity with Python programming and a background in linguistics or machine learning are often beneficial for such roles.

Is spaCy still relevant?

SpaCy is a widely used open-source library for natural language processing (NLP) tasks, including tokenization, named entity recognition, and part-of-speech tagging. It remains relevant for NLP roles due to its efficiency, ease of use, and active development, making it a valuable skill for data scientists and NLP engineers. Familiarity with Python and machine learning concepts enhances job prospects involving spaCy.

Which companies use spaCy?

Many companies across industries use spaCy for natural language processing tasks, including tech firms, financial institutions, and healthcare organizations. It is popular among data scientists and developers for building NLP applications due to its efficiency and ease of use.

What is spaCy used for?

SpaCy is a popular open-source library used by NLP professionals and data scientists for natural language processing tasks such as tokenization, part-of-speech tagging, named entity recognition, and dependency parsing. It is designed for efficient processing of large text datasets and integrates well with machine learning workflows. Knowledge of Python and NLP concepts is helpful when working with spaCy in a professional setting.

What is the meaning of spaCy?

In the context of a job related to natural language processing, spaCy is an open-source software library used for advanced text analysis and processing. It provides tools for tasks such as tokenization, part-of-speech tagging, and named entity recognition, often used by data scientists and NLP engineers. Proficiency with Python and understanding of NLP concepts are typically required for roles involving spaCy.
More about Spacy jobs
What are the most commonly searched types of Spacy jobs? The most popular types of Spacy jobs are:
Infographic showing various Spacy job openings in the United States as of July 2026, with employment types broken down into 97% Full Time, 2% Part Time, and 1% Contract. Highlights an 78% Physical, 4% Hybrid, and 18% Remote job distribution, with an average salary of $141,976 per year, or $68.3 per hour.
Senior Data Scientist

Senior Data Scientist

Centurion Consulting Group

Woodlawn, MD • On-site

$200K - $210K/yr

Other

Re-posted 23 days ago


Job description

Job Description Centurion is seeking a Senior Data Scientist to join their team to support a federal program located in Woodlawn, MD. Position Description: Hands on experience in Python, NLP frameworks, SQL, Pandas, NLTK, SPACy and LLMs Well versed in SQL and analyzing trends and transactional data. Understand real world challenges and develop automated data solutions Develop, test, and deploy new techniques for NLP understanding Scalable development/deployment of ML and Generative AI approaches (such as Large Language Models (LLMs) Train and optimize NLP/LLM models and create Python based pipelines Experience building cloud native solutions on AWS Determine the nature of analytic problems, evaluate options, and offer recommendations for resolution.

Advise on the methods and data needed and/or available to evaluate the (intelligence or data) problem. Collaborate with data collectors and analysts to identify and close gaps on complex monitoring problems. Provide accurate, timely, complex, and sophisticated data analysis.

REQUIRED SKILLS: Bachelor's degree in Statistics, Applied Mathematics, Computer Science, or Information Science with industry experience on Python, NLP frameworks, SQL, Pandas, NLTK and SPACy, data science, and AI/ML/LLM engineering. Overall 10+ years' experience in IT industry Factors To Help You Shine (Required Skills) *Selected candidate must be able to obtain and maintain a public trust clearance** *Selected candidate must be willing to work on-site in Woodlawn, MD 5 days a week** *Master's and 10+ years of experience, Bachelor's and 12+ years of experience or 18+ years in lieu of a degree** Solid Experience with Natural Language Processing (NLP), Python, NLP frameworks, SQL, Pandas, NLTK and SPACy. Experience with Generative AI and Large Language Models (LLM) Evidence of true self-starter and operating independently.

Fluency in Python Programming, version control and collaboration with GIT, standard Python packages (ex. Pandas, numpy, matplotlib) and ML frameworks Knowledge of TensorFlow, PyTorch, Pandas, scikit-learn, NLTK, Azure ML (optional), Amazon Web Services EC2. Experience with scalable data engineering frameworks such as Apache Spark and orchestration frameworks such as Airflow, and/or experience with semantic search.

Expert knowledge in conducting data analysis and applying advanced statistical concepts and ML methods to build, train, test, and evaluate a variety of supervised and unsupervised analytic models. Experience with ML model deployment and operations like DevOps, MLOps, LLMOps. Experience with NLP and Generative AI libraries like regular expressions (e.g., spacy, langchain), text annotation tools and semantic frameworks

Ability to clean and process large amounts of real-world data. Experience retrieving and manipulating data from a variety of data sources included DB2, Oracle, SQL Server, Hadoop and flat files. Excellent Communication skills.

Experience with database management systems (e.g., PostgresSQL, MySQL, SQLite, SQL, etc.) Excellent analytical skills to identify potential risks and propose effective solutions. Excellent problem-solving skills, ability to collaborate with cross-functional teams and proven communication in written and verbal formats to various audiences to include executive leadership. DESIRED SKILLS: Prior experience with federal or state governments IT projects

Industry experience preferred Experience with, or the ability and willingness to learn distributed processing via the Hadoop ecosystem, i.e., Spark, Impala and Hive. Experience working in an analytical research environment. Experience in parallel processing such as GPU programming with CUDA Experience with Mathematica Experience using markup languages such as LaTeX, HTML, etc

Experience with Natural Language Processing for anomaly detection