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Google Natural Language Processing Jobs (NOW HIRING)

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Senior AI Engineer

Coppell, TX · On-site

$96K - $132K/yr

... Natural Language Processing (NLP). • Understand multi-agent system collaboration and operation. • Deploy AI models using cloud platforms like AWS, Google Cloud, or Azure. • Design AI-driven ...

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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 Technical Architect (AI/ML) : Auburn HIlls, MI : W2 only

Senior Technical Architect (AI/ML) : Auburn HIlls, MI : W2 only

Marvel Technologies Inc

Auburn Hills, MI • On-site

Contractor

Posted 20 days ago

Job description

Senior Technical AI/ML Architect- (w2 only & Hybrid)

Auburn HIlls, MI 

We are seeking an experienced Senior Technical AI Architect with expertise in Artificial Intelligence (AI) and Machine Learning (ML), specializing in Google's suite of AI products. The ideal candidate will have a proven track record in designing and implementing advanced chatbot solutions that serve as intelligent agents, capable of providing information from company-approved data sources tailored to specific customer needs.  

Key Responsibilities:

  • Lead the architecture and design of AI/ML solutions, with a primary focus on chatbot development using Google's AI products.
  • Develop sophisticated chatbots that can act as intelligent agents, integrating with company-approved data sources to provide accurate and relevant information to customers.
  • Design and implement natural language processing (NLP) and natural language understanding (NLU) systems to enhance chatbot interactions.
  • Architect scalable and secure solutions for deploying AI models and chatbots in production environments.
  • Collaborate with data scientists, software engineers, and product managers to align AI solutions with business objectives and customer needs.
  • Evaluate and integrate various data sources, ensuring chatbots can access and utilize company-approved information effectively.
  • Implement personalization and context-aware features in chatbots to enhance user experience.
  • Develop strategies for continuous improvement of chatbot performance through machine learning and user feedback.
  • Ensure compliance with data privacy regulations and company policies in all AI/ML implementations.
  • Provide technical leadership and mentoring to the AI/ML development team.
  • Prior experience of tread reporting is mandatory
  • Prior experience of NHTSA is mandatory.

Extensive experience with Google's AI products, including but not limited to:

  • Google Cloud AI Platform
  • Dialogflow
  • Cloud Natural Language API
  • Cloud Translation API
  • TensorFlow
  • Proven track record of designing and implementing successful chatbot solutions that serve as intelligent agents.
  • Strong understanding of NLP, NLU, and machine learning algorithms.
  • Experience integrating chatbots with various data sources and APIs.
  • Proficiency in programming languages commonly used in AI/ML development (e.g., Python, Java, Go).
  • Familiarity with cloud platforms, preferably Google Cloud Platform (GCP).
  • Knowledge of data privacy regulations and best practices for secure AI implementations. 

Education:

  • Master's degree or Ph.D. in Computer Science, Artificial Intelligence, or a related field.
  • 8+ years of experience in AI/ML architecture, with at least 5 years focusing on chatbot development.