ZipRecruiter

Log In

1

Google Natural Language Processing Jobs (NOW HIRING)

Google

Research Software Engineer

Mountain View, CA · On-site

$241K/yr

... natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities ...

Conversica, Inc

Data Scientist

Seattle, WA · On-site

Conversica is seeking talented and passionate data scientists to help us evolve our artificial intelligence, machine learning and natural language processing systems and technologies. YOUR ...

Photon

Gen AI Engineer -McKinney, TX

Dallas, TX · On-site

Integrate prompt designs into natural language processing (NLP) models. * Ensure seamless ... Kore.AI, Google Dialog Flow, Amelia, Yellow.AI * Familiarity with popular conversational AI ...

Photon

Gen AI Engineer -McKinney, TX

Dallas, TX

Integrate prompt designs into natural language processing (NLP) models. * Ensure seamless ... Kore.AI, Google Dialog Flow, Amelia, Yellow.AI * Familiarity with popular conversational AI ...

Google

Software Engineer, Google Cloud Storage

Raleigh, NC · On-site

$58.25 - $75.75/hr

... natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google's needs with opportunities ...

next page

Showing results 1-20

All JobsGoogle Natural Language Processing Jobs

Google Natural Language Processing information

What is Google Natural Language Processing and what does it do?

Google Natural Language Processing (NLP) refers to a suite of tools and APIs provided by Google that enable computers to understand, analyze, and interpret human language. These tools can extract information such as sentiment, entities, syntax, and content classification from text. Businesses and developers use Google NLP to automate text analysis, improve search functionality, and enhance customer experiences through chatbots and other applications. The technology leverages advanced machine learning models to process large volumes of unstructured text data efficiently.

What is the difference between Google Natural Language Processing vs Data Scientist?

AspectGoogle Natural Language ProcessingData Scientist
Required CredentialsBackground in NLP, machine learning, computer scienceDegree in statistics, computer science, or related fields
Work EnvironmentTech companies, AI research labs, cloud service providersData-driven organizations across various industries
Employer & Industry UsageUtilized for NLP tasks like sentiment analysis, entity recognitionAnalyzes data patterns, builds predictive models, interprets complex datasets

Google Natural Language Processing specialists focus on developing and applying NLP techniques using tools like Google's APIs, while Data Scientists analyze data to extract insights and build models. Both roles require strong technical skills, but their core functions differ: NLP experts specialize in language processing, whereas Data Scientists work broadly with data analysis and modeling.

What are the key skills and qualifications needed to thrive as a Natural Language Processing (NLP) Specialist at Google, and why are they important?

To thrive as a Google Natural Language Processing Specialist, you need a strong background in computer science, linguistics, and machine learning, often supported by an advanced degree in a related field. Expertise with programming languages like Python, NLP frameworks (such as TensorFlow or PyTorch), and experience with large-scale data processing systems are typically required. Strong problem-solving, innovation, and collaborative communication skills help you excel in dynamic, multidisciplinary teams. These skills ensure the development of cutting-edge NLP solutions that power Google's products and services at scale.

What are some common challenges faced when working in a Google Natural Language Processing role, and how can they be addressed?

Professionals in Google Natural Language Processing often encounter challenges such as handling large-scale, ambiguous, or multilingual datasets and ensuring models remain unbiased and accurate across diverse applications. Collaborating with cross-functional teams, including data engineers and product managers, is essential to refine model outputs and align them with business goals. Regularly participating in code reviews, knowledge-sharing sessions, and staying updated with the latest research helps address these challenges effectively. Google supports continuous learning and encourages experimentation to drive innovation and overcome obstacles in NLP tasks.
Infographic showing various Google Natural Language Processing job openings in the United States as of June 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 69% Physical, 3% Hybrid, and 28% Remote job distribution.

Senior Software Engineer, Machine Learning, Google Cloud Compute

Google

Kirkland, WA • On-site

$139K - $183K/yr

Full-time

Posted 15 days ago

Google rating

8.8

Company rating: 8.8 out of 10

Based on 94 frontline employees who took The Breakroom Quiz

32nd of 191 rated software companies

Job description

Job Summary:
Google is a leading technology company that develops next-generation technologies impacting billions of users. The Senior Software Engineer in Machine Learning will design, develop, test, deploy, maintain, and enhance software solutions, while managing project priorities and deliverables.
Responsibilities:
• Write and test product or system development code.
• Participate in, or lead design reviews with peers and stakeholders to decide amongst available technologies.
• Review code developed by other developers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
Qualifications:
Required:
• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages, and with data structures/algorithms.
• 3 years of experience testing, maintaining or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience with ML/AI algorithms and tools, deep learning or natural language processing.
Preferred:
• Master's degree or PhD in Computer Science or a related technical field.
• 1 year of experience in a technical leadership role.
• Experience in developing accessible technologies.
Company:
Google specializes in internet-related services and products, including search, advertising, and software. It is a sub-organization of Alphabet. Founded in 1998, the company is headquartered in Mountain View, USA, with a team of 10001+ employees. The company is currently Late Stage.

What Google employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom

Apply