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Spacy Jobs (NOW HIRING)

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RAKOF 415 PYTHON DEVELOPER

Princeton, NJ · On-site

$52.75 - $72.50/hr

Understand the Python software development stacks, ecosystems, frameworks and tools such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, sci-kit-learn and PyTorch. Involved front-end development using ...

Zenlaw

Data Scientist (Remote)

New York, NY · On-site +1

Our wide range of experience includes NLP, SpaCy, Transformers, and PyTorch recommendation systems, supervised and unsupervised problems. As part of the team, you are free to use the approach you see ...

JS Consulting

Data Scientist

Washington, DC · On-site

Vector DB, BERT, RoBERTa (or comparable tools), Spacy, LLM and GenAI tools. Experience with LoRA, LangChain, RAG, LLM Fine Tuning and PEFT, Knowledge Graphs. * Strong skills in developing GraphRAG ...

Tata Consultancy Service Limited

Engineer

Owings Mills, MD · On-site

$80K - $90K/yr

Experience with natural language processing (NLP) techniques and tools, such as SpaCy, NLTK, or Hugging Face. 6.Need to have knowledge of software development methodologies, such as Agile or Scrum. 7.

Infosys

Solutions Architect

Tampa, FL · On-site

$59.50 - $78.50/hr

OAP, VEGAS, PyVegas), Advanced NLP, LangChain, Spacy. Data Migration: Apache Airflow Databases: Oracle 11g, MySQL, MS SQL Server, Redis (In-memory). Programming: Python, Shell scripting, SQL, PL/SQL ...

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 ...

Infosys Limited Digital

Solutions Architect

Tampa, FL · On-site

$59.50 - $78.50/hr

OAP, VEGAS, PyVegas), Advanced NLP, LangChain, Spacy. Data Migration: Apache Airflow Databases: Oracle 11g, MySQL, MS SQL Server, Redis (In-memory). Programming: Python, Shell scripting, SQL, PL/SQL ...

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Spacy information

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$55K

$142K

$195K

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:
What job categories do people searching Spacy jobs look for? The top searched job categories for Spacy jobs are:
Spacy jobs near you
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.
Data Engineer - Aurora, CO or Meridian, CO

Data Engineer - Aurora, CO or Meridian, CO

ICR, Inc.

Aurora, CO

$100K - $167K/yr

Full-time

Medical, Retirement, PTO

Re-posted 9 days ago

Job description

Data Engineer
Aurora, CO or Meridian, CO (Location is at program discretion)
Applications will be accepted on an ongoing basis.
Required Skills and Qualifications
  • Active Top Secret Security Clearance with SSBI and SCI eligibility
  • Bachelor's degree in Computer Science, Computer Engineering or a related field.
  • Proficient in Python
  • High level of self-initiative and self-motivation

Desired Skills
  • Experience in using NLP tools (Spacy, Stanford, Bert...)
  • Experience with ESRI ArcGIS products
  • Experience with service-oriented architectures
Salary Range: $100,000 - $167,565
This position offers a comprehensive benefits package that includes company equity, retirement plan, company-paid health care benefits, flexible paid time off policy, and opportunity for a raise and bonus during the year.
ICR, Inc. considers several factors when extending job offers, including but not limited to candidates’ key skills, relevant work and/or military experience, education, training, certifications and work location.
ICR is proud to be an equal opportunity employer and considers qualified applicants for employment without regard to race, color, creed, religion, national origin, sex, sexual orientation, gender identity and expression, age, disability, veteran status, or any other protected factor.

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