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Machine Learning Nlp Jobs in Texas (NOW HIRING)

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... Apply a broad range of modelling techniques - including time-series forecasting, NLP ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... Apply a broad range of modelling techniques - including time-series forecasting, NLP ...

Vitol

Senior Machine Learning Engineer

Houston, TX · On-site

$117K - $154K/yr

The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow ... Apply a broad range of modelling techniques - including time-series forecasting, NLP ...

Tata Consultancy Service Limited

Data scientist

Addison, TX · On-site

$120K - $140K/yr

The ideal candidate will have a solid background in software engineering with experience in building Machine Learning NLP Models and good familiarity with Gen AI Models. Mandatory In office policy ...

New

Sarian, Inc.

Sr. Data Scientist

Irving, TX · On-site

Machine learning, NLP & deep learning: Strong understanding of supervised and unsupervised learning, neural networks, transformers * Generative AI techniques: Experience with GANs, text-to-image ...

T-Mobile

Sr Engineers, Machine Learning

Frisco, TX · On-site

$97K - $134K/yr

Translate complex machine learning concepts and model behaviors into actionable insights for ... Experience (3) Experience designing and deploying NLP and semantic understanding systems including ...

Syntricate Technologies

Data Scientist

Dallas, TX · On-site

Python (proficient) with major Client libraries • Experience with opensource Gen AI LLMs e.g., Llama and Dolly • Machine learning, NLP & deep learning: Strong understanding of supervised and ...

Tata Consultancy Service Limited

Engineer

Irving, TX · On-site

$80K - $90K/yr

Python (proficient) with major ML libraries • Experience with opensource Gen AI LLMs e.g., Llama and Dolly • Machine learning, NLP & deep learning: Strong understanding of supervised and ...

Apex Informatics

Data Scientist

Addison, TX · On-site

The ideal candidate will have a solid background in software engineering with experience in building Machine Learning NLP Models and good familiarity with Gen AI Models. REQUIRED SKILLS * 7+ years of ...

Beth Page tech

Senior Machine Learning Engineer

Houston, TX · On-site

$99K - $137K/yr

Senior Machine Learning Engineer Location: Houston, TX Environment: Standard, 5-days onsite : Must ... Practical application of NLP techniques (sentiment analysis, entity recognition) and knowledge ...

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Showing results 21-40

All JobsMachine Learning Nlp JobsMachine Learning Nlp Jobs in Texas

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 10, 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 are popular job titles related to Machine Learning Nlp jobs in Texas?

For Machine Learning Nlp jobs in Texas, the most frequently searched job titles are:

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:

Machine Learning Nlp jobs near you
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.

Senior Machine Learning Engineer

Houston, TX • On-site

Vitol
See more jobs at Vitolexternal

$117K - $154K/yr

Full-time

Re-posted 5 days ago

Job description

Company Description
Vitol is an energy and commodities company with revenues of $400 billion in 2023; its primary business is the trading and distribution of energy products globally - it trades over seven million barrels per day of crude oil and products and, at any time, has 250 ships transporting its cargoes.
Vitol's clients include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves clients from some 40 offices worldwide and is invested in energy assets globally including 16mm3 of storage, 480kbpd of refining capacity, and 7,000 service stations. To date, we have committed over $2.5 billion of capital to renewable projects, and are identifying and developing low-carbon opportunities around the world. Learn more about us here.
This Role is located in Houston, TX - In office 5x a week
Job Description
As our portfolio of work continues to grow, we are looking for an experienced Machine Learning Engineer to join our data science and machine learning team. The individual will work closely with the data and machine learning specialists, software engineers and commercial teams to deliver machine learning models and applications. We work across the trading business, operations, and other support functions; so the individual will need to be comfortable working with a variety of stakeholders and technologies.
The Machine Learning Engineer at Vitol has visibility and impact across the full project workflow: from working with business stakeholders to help define the project, to data collation and processing, exploratory analysis, model selection and tuning, and implementation of production models.
The successful candidate will join a team of experienced, collaborative practitioners, who are (pragmatically) solving some of the most challenging and impactful problems the energy industry is facing; as well as pushing the boundaries around the 'art of the possible'.
Core Responsibilities include:
  • Design, develop, and deploy end-to-end machine learning and data science solutions across our wider business activities (including trading, operations, and support functions) - from raw data ingestion through to production-grade models and monitoring
  • Drive adoption and development of the firm's internal GenAI chat platform as one of the technical leads, extending its capabilities through new integrations, data connectors, and domain-specific prompt engineering; work closely with trading desks and operational teams to identify high-value use cases, embed the tool into day-to-day workflows, and ensure outputs are robust, and trusted by end users.
  • Apply a broad range of modelling techniques - including time-series forecasting, NLP, classification, and generative AI - to commodity pricing, supply/demand signals, trade flow analysis, and operational optimization problems
  • Own the full data science lifecycle on assigned projects: data sourcing and cleaning, exploratory analysis, feature engineering, model selection and validation, deployment, and ongoing performance monitoring
  • Build and maintain robust, well-tested, production-quality code; contribute to shared infrastructure including ML pipelines, data orchestration, and model serving layers
  • Integrate ML and GenAI outputs into existing trading systems, dashboards, and workflows; work with software engineers to ensure reliable, scalable adoption across the business
  • Communicate analytical findings and model outputs clearly to non-technical stakeholders; present results, assumptions, and limitations in a manner that supports confident commercial decision-making
  • Actively participate in code reviews, experiment design, and tooling decisions; mentor colleagues and help raise the overall standard of analytical and engineering practice across the team

Qualifications
  • Master's degree or equivalent in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field
  • Fluency in Python for both data science and engineering purposes: clean, modular, well-documented code, with strong understanding of software engineering best practices including version control, testing, and code review
  • 5+ years of industry experience developing and deploying machine learning or statistical models, with a proven track record of delivering end-to-end solutions in production environments
  • Demonstrable experience applying a broad range of ML methodologies (supervised and unsupervised learning, time-series modelling, NLP/LLMs, optimization) to real-world business problems
  • Strong proficiency with ML frameworks (e.g. PyTorch, scikit-learn, Transformers) and experience building or consuming LLM-based pipelines and GenAI applications
  • Experience with cloud platforms (AWS preferred) and modern MLOps practices: containerization (Docker/Kubernetes), CI/CD, data pipeline orchestration (e.g. Airflow, Dagster), and model serving
  • Strong analytical and problem-solving ability: capable of defining and scoping open-ended problems, proposing sound methodological approaches, and defending modelling choices with rigorous reasoning
  • Excellent written and verbal communication skills, with the confidence to present model outputs, caveats, and commercial implications clearly to non-technical audiences including traders and senior management
  • Genuine intellectual curiosity about commodities markets, global energy flows, and the commercial dynamics of trading; willingness to develop domain knowledge as part of the role

Desirable Experience
  • Experience in the energy or commodities trading industry, with knowledge of financial markets and trading concepts
  • Experience surfacing ML outputs through interactive tools (e.g. Dash, Streamlit, or similar) and presenting use cases to non-technical audiences, including traders and senior management
  • Time-series modelling in a trading or financial context, including both ML-based and econometric approaches (e.g. ARIMA, cointegration, regime-switching models)
  • Data orchestrators (Airflow, Dagster) and cloud-based ETL/ELT pipelines

Additional Information
Personal Characteristics
  • A self-motivated individual who thrives on seeing the results of their work make an impact in the business
  • Pragmatic and delivery-focused: comfortable navigating ambiguity, balancing rigor with speed, and making sound judgements under uncertainty
  • Methodical and detail-oriented: rigorous in experimental design, data validation, and code quality, with a disciplined approach to documenting assumptions and results
  • Resourceful, able to think creatively and adapt in a dynamic environment
  • Team player, with an open non-political style and a high level of integrity
  • Desire to be a thought-partner in a fast-growing team, and make an impact at a business that sits at the heart of the world's energy flows

Work Environment
  • This job operates in a professional office environment. Because of the collaborative, fast-paced, and high energy nature of our business, Vitol requires team members to work from our fully-equipped office.

What we offer
  • Competitive salary and benefits package
  • Large diversity of projects with real-world impacts on a truly global scale
  • Entrepreneurial environment within a flat hierarchy, where great ideas come to life quickly
  • Close collaboration with various business units across our key regions (eg. London, Singapore, Houston, Geneva)
  • A highly motivated DS and ML team comprised of experienced individuals with a supportive attitude and great team spirit
  • Being part of the energy transition through increased emphasis on renewable & alternative energy sources at a pivotal moment in the industry
  • Strong management commitment to incorporating machine learning into the future of Vitol's operations

All your information will be kept confidential according to EEO guidelines.

Apply