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Language Model Jobs in Queens, NY (NOW HIRING)

NOUS RESEARCH

Research Scientist

New York, NY · On-site

Lead, collaborate, and execute on research that pushes forward the state of the art in large language model research * Contribute to Conference-quality publications and open-sourcing efforts * Help ...

Slalom Consulting

General Information

New York, NY · On-site

Lead the design and delivery of enterprise AI solutions using Anthropic technologies, including large language model integrations, agentic workflows, and retrieval-augmented generation pipelines, to ...

Baseten

Software Engineer - Model Performance

New York, NY · On-site

$180K - $360K/yr

Apply and scale optimization techniques across a wide range of ML models, particularly large language models. * Collaborate with a diverse team to design and implement innovative solutions. * Own ...

StackAI

Forward Deployed AI Engineer

New York, NY · On-site

$153K - $200K/yr

You will integrate large language models into enterprise operations, working with strategic accounts to align solutions and technical approaches. Using the Stack AI platform, you'll also partner with ...

Saransh Inc

AI Architect - Remote

New York, NY · On-site

Experience with Small Language Models (SLM), Agent-to-Agent (A2A) communication, and Model Context Protocol (MCP). * Proven ability to architect and scale AI solutions for enterprise workloads (1M ...

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Showing results 21-40

All JobsLanguage Model JobsLanguage Model Jobs in Queens, NY

Language Model information

See Queens, NY salary details

$10

$32

$69

How much do language model jobs pay per hour?

As of Aug 13, 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 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 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 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 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:
Language Model jobs near you

Applied AI ML Lead - Generative AI and Semantic Modeling

JPMorgan Chase & Co.

Jersey City, NJ • On-site

$171K - $260K/yr

Full-time

Medical, Retirement

Re-posted 8 hours ago

JPMorgan Chase & Co. rating

8.0

Company rating: 8.0 out of 10

Based on 493 frontline employees who took The Breakroom Quiz

71st of 171 rated banks

Job description


You will help shape how analytics and generative AI are delivered at enterprise scale-turning complex business problems into production-ready, measurable solutions. You will work with a collaborative team that values engineering excellence, responsible innovation, and continuous learning.
As an Applied AI and Machine Learning Lead at JPMorganChase within Corporate Technology Data Science and AI, you will design, build, and deploy scalable analytical and generative AI solutions that deliver measurable business value. You will partner with stakeholders to shape problem statements, define success metrics, and deliver production-ready models and intelligent workflows. You will help establish semantic modeling standards and a unified semantic layer that improves trust and consistency across analytics and AI use cases.
Job responsibilities
  • Develop generative AI, agent-based AI, and large language model solutions in Python from proof of concept through production deployment
  • Design context engineering approaches to improve model accuracy, latency, reliability, and overall performance in real-world workflows
  • Lead semantic modeling strategy, including ontology standards, governance, and lifecycle management aligned to enterprise needs
  • Create scalable ontologies that model business entities, relationships, rules, and constraints in partnership with domain experts
  • Define semantic integration patterns across data pipelines, application programming interfaces, data contracts, and experience layers to resolve semantic conflicts
  • Build and govern a unified semantic layer that enables trusted analytics across business intelligence, machine learning, and transactional systems
  • Enable intelligent workflows and AI agents using ontology-driven context, semantic reasoning, and orchestration methods
  • Build and maintain pipelines and frameworks for model training, evaluation, optimization, monitoring, and production operations
  • Implement responsible AI practices, model risk controls, and governance aligned to regulated environments and internal standards
  • Communicate complex technical concepts clearly to technical and non-technical stakeholders, including senior leaders, to align delivery to business objectives

Required qualifications, capabilities and skills
  • Master's degree in a data science-related discipline and 8 years of industry experience, or a PhD in a data science-related discipline
  • Hands-on experience developing and deploying machine learning and generative AI solutions using Python
  • Demonstrated ability to write and maintain production-quality code, including reliability, performance, and maintainability considerations
  • Experience with continuous integration practices and unit test development to support quality delivery
  • Experience building and managing data pipelines and processing workflows that support analytical and machine learning use cases
  • Strong written and verbal communication skills, including the ability to translate technical decisions into business impact
  • Demonstrated scientific thinking and structured problem-solving skills for ambiguous, data-driven challenges
  • Ability to work independently while collaborating effectively across product, engineering, and business stakeholders

Preferred qualifications, capabilities and skills
  • Experience building large language model applications that use context engineering to improve response quality and reliability
  • Background in semantic modeling, ontology design, and governance practices in enterprise environments
  • Experience designing semantic integration patterns across data contracts and application programming interfaces in distributed systems
  • Experience implementing monitoring and evaluation approaches for machine learning and generative AI in production
  • Experience mentoring data scientists and engineers and promoting modern machine learning engineering best practices

#LI-RB3
About Us
JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.
We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process.
We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.
JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans
About the Team
Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.

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