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Machine Learning Nlp Jobs in Texas (NOW HIRING)

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Keep a pulse on the latest advancements in NLP, LLMs, and agentic AI research, and act as a subject ...

Lead Machine Learning Engineer

Houston, TX · On-site +1

$97K - $128K/yr

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI ... Keep a pulse on the latest advancements in NLP, LLMs, and agentic AI research, and act as a subject ...

Databricks Data Architect

Austin, TX · On-site

$63.25 - $81.25/hr

Machine Learning, Deep Learning, NLP, or Generative AI * Designing distributed and scalable systems * API-first and microservices architecture * Python, ML frameworks (TensorFlow, PyTorch, Scikit ...

Databricks Data Architect

Austin, TX · On-site

$63.25 - $81.25/hr

Machine Learning, Deep Learning, NLP, or Generative AI * Designing distributed and scalable systems * API-first and microservices architecture * Python, ML frameworks (TensorFlow, PyTorch, Scikit ...

Director of AI Engineering

Sugar Land, TX · On-site

$143K - $205K/yr

Machine Learning & AI: Deep learning, NLP, generative AI, predictive analytics, reinforcement learning. MLOps & AI Engineering: Model deployment, cloud-based AI solutions, automation, monitoring, and ...

Showing results 41-60

Machine Learning Nlp information

See Texas salary details

$34.9K

$114.3K

$183.1K

How much do machine learning nlp jobs pay per year?

As of Sep 13, 2026, the average yearly pay for machine learning nlp in Texas is $114,350.00, according to ZipRecruiter salary data. Most workers in this role earn between $91,800.00 and $126,700.00 per year, depending on experience, location, and employer.

What is a machine learning NLP?

A Machine Learning NLP job involves developing algorithms and models that enable machines to understand, process, and generate human language. Professionals in this role work with large datasets, train models on text data, and fine-tune natural language processing techniques such as sentiment analysis, text classification, and language translation. They often use machine learning frameworks like TensorFlow, PyTorch, and NLP libraries such as spaCy or Hugging Face Transformers. The goal is to build intelligent applications, including chatbots, search engines, and automated content analysis systems.

What does a machine learning NLP do?

As a Machine Learning NLP specialist, your daily responsibilities often include designing and implementing NLP models, cleaning and preprocessing large text datasets, and experimenting with algorithms to improve model performance. You may also evaluate model results, collaborate with software engineers and data scientists, and stay updated on the latest research in the field. Frequent code reviews, participation in team meetings, and contributing to documentation are also common. This role combines hands-on technical work with collaborative problem-solving to develop language-based AI solutions for real-world applications.

What are the key skills and qualifications needed to thrive in the machine learning NLP position?

To thrive as a Machine Learning NLP professional, you need a strong background in machine learning, natural language processing, data analysis, and proficiency in programming languages such as Python, typically supported by a relevant degree in computer science or related field. Familiarity with NLP libraries (like spaCy, NLTK, or Hugging Face), machine learning frameworks (such as TensorFlow or PyTorch), and experience with cloud platforms are highly valued, and certifications can enhance your profile. Strong problem-solving skills, effective communication abilities, and adaptability are important soft skills in this role. These competencies enable you to build sophisticated language models and efficiently collaborate on cross-functional projects in a rapidly evolving technical landscape.

Are machine learning NLP engineers in demand?

Machine learning NLP engineers are in high demand due to the growing use of natural language processing in applications like chatbots, virtual assistants, and data analysis. Companies seek professionals skilled in deep learning frameworks, Python, and NLP tools to develop and improve AI language models, making this a strong career field with positive job growth prospects.

What job categories do people searching Machine Learning Nlp jobs in Texas look for?

The top searched job categories for Machine Learning Nlp jobs in Texas are:

Infographic showing various Machine Learning Nlp job openings in Texas as of August 2026, with employment types broken down into 1% As Needed, 78% Full Time, 20% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $114,350 per year, or $55 per hour.

Lead Machine Learning Engineer

Houston, TX • On-site, Remote

NobleAI
IT Services • 11 - 50 employees

$97K - $128K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 22 days ago


Job description

At NobleAI, we believe that energy, material science and chemistry are key to building a sustainable world and that artificial intelligence is essential to unlock this potential. NobleAI leverages innovative Science-Based AI technology to revolutionize energy workflows, materials development, and chemical designs. We enable companies to accelerate innovation and reduce costs in developing sustainable technologies and products. 

We're a team of excellence-driven individuals who value thoughtfulness and respect while focusing on delivering products that empower engineers and researchers to create better solutions faster.

At NobleAI, we are developing the next generation of intelligent chemical informatics platform. Our goal is to create a seamless, intuitive experience that empowers users to achieve unprecedented productivity in data processing, visualization, and model building. We are seeking a forward-thinking team member who thrives on innovation, collaboration, and rapid iteration, and has the ability to solve challenging problems in science and technology. 

As a Lead Machine Learning Engineer specializing in conversational and agentic systems at NobleAI, you will be responsible for architecting, building, and deploying intelligent features to our VIP platform. This role is ideal for individuals passionate about the cutting edge of LLMs and eager to build AI systems that can reason, plan, and act. 

Join us in building a more sustainable world through the power of AI and scientific innovation.

Requirements

  • Design domain specific AI systems and chatbots capable of complex dialogue management and workflow execution via tools, API calls and multi step tasks based on user goals, multi-agent orchestration.
  • Collaborate with scientists to assess, fine-tune, and deploy LLMs on domain specific data to support accuracy measurement for use cases
  • Build and maintain Retrieval-Augmented-Generation (RAG) systems, Reinforcement Learning frameworks, guardrail and assessment mechanisms for end to end lifecycle for customized models.
  • Collaborate with product and software engineers to integrate the features into our platform.
  • Establish prompt engineering and data management best practices for transparency and governance.
  • Establish best practices for monitoring and evaluation of data and models across the model lifecycle (development, testing, and production)
  • Keep a pulse on the latest advancements in NLP, LLMs, and agentic AI research, and act as a subject matter expert on architecture decisions on platform and use cases.


What We're Looking For

  • MSc (preferred) or BSc in Computer Science, Artificial Intelligence, or a related quantitative field.
  • 5+ years of hands-on experience building and deploying AI/ML systems, with a strong focus on Natural Language Processing (NLP).
  • Proven experience designing and shipping chatbots, virtual assistants, or agentic systems using modern LLM-based architectures.
  • Strong programming proficiency in Python (5+ years) and deep experience with core ML/NLP libraries such as PyTorch, TensorFlow
  • Hands-on experience with LLM agent frameworks for building complex, tool-using applications, multi-agent orchestration, or establishing MCP services for platform capabilities.
  • Demonstrated experience with Retrieval-Augmented Generation (RAG), including the use of vector databases like Pinecone, Weaviate, or ChromaDB.
  • Familiarity with techniques for fine-tuning LLMs (e.g., LoRA/QLoRA) and experience working with open-source models (e.g., Llama, Mistral) or major model APIs (e.g., OpenAI, Anthropic).
  • 5+ years of experience with cloud platforms (Azure preferred) and familiarity with deploying AI models as scalable microservices using Docker and Kubernetes (KFP, KServe).
  • Solid software engineering fundamentals, including version control (Git), automated testing, and CI/CD principles.
  • Excellent communication skills with the ability to articulate complex technical ideas to both technical and non-technical stakeholders.

Benefits

We offer great pay & benefits.

  • Top-tier health benefits coverage, including medical, dental, vision, disability and life insurance
  • Flexible paid time off & generous holidays
  • Remote-first with co-working access at Industrious offices
  • 401(k) with employer match 
  • Equity package
  • Salary Range $190,000 - $205,000 (Depending on experience & Geographic location) 
  • Performance-based bonus plan