Machine Learning Natural Language Processing information
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$17.68 is the 25th percentile. Wages below this are outliers.
$17.09 - $18.18
13% of jobs
The median wage is $19.04 / hr.
$18.18 - $19.27
24% of jobs
$19.27 - $20.37
11% of jobs
$21.30 is the 75th percentile. Wages above this are outliers.
$20.37 - $21.46
11% of jobs
$21.46 - $22.55
11% of jobs
$22.55 - $23.65
7% of jobs
$23.65 - $24.74
3% of jobs
$24.74 - $25.83
1% of jobs
$25.83 - $26.92
1% of jobs
How much do machine learning natural language processing jobs pay per hour?
As of Sep 9, 2026, the average hourly pay for machine learning natural language processing in the United States is $19.89, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $21.63 per hour, depending on experience, location, and employer.
A Machine Learning Natural Language Processing (NLP) specialist is a professional who designs, develops, and implements algorithms and models that allow computers to understand, interpret, and generate human language. They use machine learning techniques to work on tasks such as text classification, sentiment analysis, language translation, and speech recognition. NLP specialists often work with large datasets and require strong skills in programming, linguistics, and data science. Their work enables applications like chatbots, virtual assistants, and search engines to better process human language.
A Machine Learning Natural Language Processing (NLP) specialist needs strong programming skills (especially in Python), a solid understanding of machine learning algorithms, and advanced knowledge in linguistics or computational linguistics, often supported by a relevant degree. Familiarity with NLP libraries (like NLTK, spaCy, or Hugging Face Transformers), experience with machine learning frameworks (such as TensorFlow or PyTorch), and sometimes certifications in data science or AI are typically required. Excellent problem-solving ability, collaboration, and effective communication are crucial soft skills to excel in this field. These skills enable the development of robust NLP models, smooth integration into real-world applications, and effective teamwork on complex projects.
In Machine Learning Natural Language Processing (NLP) roles, collaboration with cross-functional teams is essential. NLP professionals frequently work alongside data engineers to gather and preprocess large datasets, software developers to integrate models into products, and product managers to align technical solutions with business goals. Regular communication, agile methodologies, and collaborative problem-solving sessions are common to ensure that NLP models are both technically sound and user-oriented. This teamwork not only enhances the effectiveness of NLP solutions but also provides opportunities to learn from colleagues with diverse expertise.
What cities are hiring for Machine Learning Natural Language Processing jobs?
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What states have the most Machine Learning Natural Language Processing jobs?
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