ZipRecruiter

Log In

1

Language Model Jobs in Denton, TX (NOW HIRING)

Addison Group

AI Developer

Dallas, TX · On-site

$115K - $140K/yr

Create and deploy AI-enabled applications using large language models and modern generative AI platforms. * Develop autonomous and multi-agent solutions capable of using tools, retrieving information ...

Addison Group

AI Developer

Dallas, TX · On-site

$115K - $140K/yr

Create and deploy AI-enabled applications using large language models and modern generative AI platforms. * Develop autonomous and multi-agent solutions capable of using tools, retrieving information ...

next page

Showing results 1-20

All JobsLanguage Model JobsLanguage Model Jobs in Denton, TX

Language Model information

See Denton, TX salary details

$9

$29

$62

How much do language model jobs pay per hour?

As of Sep 5, 2026, the average hourly pay for language model in Denton, TX is $29.41, according to ZipRecruiter salary data. Most workers in this role earn between $17.79 and $36.73 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 cities near Denton, TX are hiring for Language Model jobs?

Cities near Denton, TX with the most Language Model job openings:

Language Model jobs near you

AI Developer

Addison Group

Dallas, TX • On-site

$115K - $140K/yr

Other

Medical, Dental, Vision, Retirement

Posted 8 days ago

Key responsibilities

  • Create and deploy AI-enabled applications using large language models and modern generative AI platforms.

  • Develop autonomous and multi-agent solutions capable of using tools, retrieving information, and completing multistep tasks.

  • Connect Snowflake, Azure Databricks, and other enterprise data sources to AI applications and machine learning processes.

Job description

Job Title: AI Developer

Industry: Oil & Gas / Energy

Location: Dallas, Texas - onsite 5x a week

Assignment Type: Direct Hire

Pay: $115,000–$140,000 annually, plus a 15% short-term incentive and 20% long-term incentive.

Benefits: This position is eligible for medical, dental, vision, and 401(k). The company offers fully paid family benefits, a generous 401(k) match, and a competitive paid-time-off program.

Our client is an established energy organization investing in a new artificial intelligence and machine learning function. The company offers a collaborative, fast-moving environment where employees are empowered to make decisions, explore emerging technologies, and influence how AI is used across the business.

We are seeking an AI Developer to join a newly created AI/ML team and help transform emerging artificial intelligence capabilities into practical business solutions. This foundational team member will design, prototype, and deploy AI-enabled applications, intelligent agents, and automated workflows using Microsoft Azure, Azure Databricks, Azure AI Foundry, Snowflake, and modern large language model technologies.

This is a broad, hands-on role suited for an intellectually curious developer who enjoys experimenting with new tools and solving loosely defined problems. The ideal candidate combines software and data engineering fundamentals with genuine enthusiasm for generative AI. Because the field and team are still evolving, this person must be comfortable learning quickly, testing new approaches, and helping establish technical direction.

Key Responsibilities:

  • Create and deploy AI-enabled applications using large language models and modern generative AI platforms.
  • Develop autonomous and multi-agent solutions capable of using tools, retrieving information, and completing multistep tasks.
  • Build agent-based workflows using technologies such as Azure AI Foundry Agent Service, Anthropic Claude, and comparable development frameworks.
  • Connect Snowflake, Azure Databricks, and other enterprise data sources to AI applications and machine learning processes.
  • Develop and maintain reliable data pipelines using SQL, Python, dbt, or similar technologies.
  • Implement retrieval-augmented generation solutions that allow AI systems to securely use relevant organizational data.
  • Create automated evaluation and testing methods to assess the accuracy, reliability, performance, and safety of models and agents.
  • Quickly prototype emerging AI tools, frameworks, and models to determine whether they provide meaningful business value.
  • Turn ambiguous business needs into functional prototypes and scalable production solutions.
  • Partner with data scientists, data engineers, IT professionals, and business leaders throughout the development lifecycle.
  • Help establish responsible AI practices related to privacy, governance, permissions, and secure data access.
  • Document technical solutions and share findings, recommendations, and best practices with team members and stakeholders.
  • Present technical recommendations confidently and respectfully challenge assumptions when another approach may produce a better result.

Qualifications:

  • Bachelor’s degree in computer science, data science, engineering, mathematics, or a related discipline is required.
  • Two to four years of experience developing and deploying software, data, AI, or machine learning applications in a production environment.
  • Strong Python skills with experience producing organized, tested, and maintainable code.
  • Working knowledge of SQL and experience with a cloud-based data platform such as Snowflake, Databricks, or a comparable technology.
  • Practical exposure to developing applications with generative AI or large language model APIs, such as Claude, OpenAI, Azure OpenAI, or similar platforms.
  • Understanding of software engineering practices, including Git or GitHub, automated testing, CI/CD, and common application design principles.
  • Strong analytical and troubleshooting abilities with the capacity to work through unfamiliar or loosely defined problems.
  • Effective communication skills and the ability to collaborate across engineering, data science, technology, and business groups.
  • Demonstrated ability to independently learn new frameworks, platforms, and development approaches.
  • Comfort working within a newly formed team where technologies, priorities, and processes may change quickly.