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Language Model Jobs in Queens, NY (NOW HIRING)

Reality Labs at Meta is seeking a Research Scientist with deep expertise in Large Language Models (LLMs) to advance our work in AI-powered neuromotor interactions for wearable devices. We are ...

Senior AI Engineer

Iselin, NJ · Hybrid

$106K - $145K/yr

The Senior AI Engineer is a technical leader with deep expertise in AI/ML, Generative AI, Large Language Models (LLMs), and modern cloud-native application development. This role is responsible for ...

Head of AI Product

Manhattan, NY · Hybrid

$256K - $268K/yr

The successful candidate will have hands-on familiarity with the current generation of language model and search technologies, and a clear-eyed view of where they create durable commercial value ...

Head of AI Product

New York, NY · On-site

$254K - $266K/yr

The successful candidate will have hands-on familiarity with the current generation of language model and search technologies, and a clear-eyed view of where they create durable commercial value ...

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Language Model information

See Queens, NY salary details

$10

$32

$69

How much do language model jobs pay per hour?

As of Sep 7, 2026, the average hourly pay for language model in Queens, NY is $32.73, according to ZipRecruiter salary data. Most workers in this role earn between $19.81 and $40.87 per hour, depending on experience, location, and employer.

What is a language model?

Language models are artificial intelligence systems designed to understand, generate, and manipulate human language. They are trained on vast amounts of text data to predict the next word in a sequence, answer questions, write content, translate languages, and perform other language-related tasks. Modern language models, such as those based on deep learning, have revolutionized natural language processing by enabling more accurate and context-aware interactions between humans and machines.

What are the common challenges faced by professionals working on language model development teams?

Professionals developing language models often encounter challenges such as managing large datasets, addressing biases in training data, and optimizing model performance while balancing computational resources. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is essential to ensure the model's accuracy and relevance. Additionally, staying current with rapid advancements in AI research and maintaining responsible AI practices are crucial aspects of the role.

What are the key skills and qualifications needed to thrive as a language model, and why are they important?

To thrive as a Language Model Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Experience with frameworks like TensorFlow or PyTorch, and familiarity with large-scale data processing tools, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help in designing effective models and working with cross-functional teams. These capabilities are crucial for developing performant and accurate language models that meet complex real-world communication needs.

What is the difference between Language Model vs Data Scientist?

AspectLanguage ModelData Scientist
Required CredentialsNone specific; knowledge of NLP and AI concepts helpfulBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in AI applications, chatbots, content generationAnalyzing data, building models, providing insights

While both roles involve working with data and AI, a Language Model is an AI system designed to understand and generate human language, often developed by AI engineers. A Data Scientist analyzes data to extract insights and build predictive models, often utilizing language models as tools. Understanding the differences helps clarify career paths and job expectations in the AI and data fields.

What are popular job titles related to Language Model jobs in Queens, NY?

For Language Model jobs in Queens, NY, the most frequently searched job titles are:

What job categories do people searching Language Model jobs in Queens, NY look for?

The top searched job categories for Language Model jobs in Queens, NY are:

What cities near Queens, NY are hiring for Language Model jobs?

Cities near Queens, NY with the most Language Model job openings:

Staff Software Engineer, Applied AI, Model Quality

Google Inc.

Manhattan, NY • On-site

$207 - $300/hr

Other

Posted 17 days ago


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

48th of 247 rated software companies


Job description

Staff Software Engineer, Applied AI, Model Quality Advanced

Experience owning outcomes and decision making, solving ambiguous problems and influencing stakeholders;deep expertise in domain.

  • Bachelor’s degree or equivalent practical experience.
  • 8 years of experience in software development.
  • 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  • 5 years of experience with ML design and ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
  • 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.
  • Experience integrating generative AI tools or Large Language Model (LLM) interfaces into workflows.
Preferred qualifications
  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  • 8 years of experience with data structures and algorithms.
  • 3 years of experience in a technical leadership role leading project teams and setting technical direction.
  • 3 years of experience working in a complex, matrixed organization involving cross-functional, or cross-business projects.
About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, 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 to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

As a part of Google Pics, an upcoming AI-powered visual editor seamlessly integrated across Google Workspace to bring Gen-AI photo and design capabilities directly onto the canvas. In this role, you will work with the advanced image-understanding capabilities of GemPix and Gemini to empower users to intuitively edit, transform, and generate images across all Workspace surfaces. In this role, you will be executing against a 2026 roadmap, building on limited testing and consumer experiments ahead of a General Availability (GA) launch in 2026. You will join a team that requires executing at a fast pace against a comprehensive roadmap of model capabilities. Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $207000 - $300000 (USD) + 20% bonus target + equity + benefits

Learn more about benefits at Google .

  • Build both human-powered and Large Language Model (LLM)-powered automated evaluation systems to assess model performance.
  • Establish clear metrics to measure aspects like grounding, coherence, safety, and helpfulness.
  • Utilize platforms and tools to efficiently run evaluations across different models and datasets.
  • Provide actionable insights from evaluations to improve model quality, often in collaboration with research, and cross-functional teams.
  • Create tools and systems that make the evaluation process more efficient and effective.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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