AI Engineer Jobs in Texas
AI Engineer jobs in Texas are among the most actively recruited technology roles in the country, with demand concentrated in enterprise software, defense and aerospace, energy technology, and financial services at levels from entry-level to principal. Austin, Dallas, and Houston lead hiring volume, and established employers such as Dell Technologies, Lockheed Martin, and ExxonMobil consistently staff ai engineer teams in the state. The most in-demand specialties are large language model development, MLOps and model deployment, and computer vision applied to industrial and energy systems. Find a role that fits below and apply directly.
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Role: Senior Azure AI Document Intelligence Engineer (OCR Experience)
We are seeking a Senior Azure AI Document Intelligence Engineer responsible for designing, training, and optimizing AI-powered contract and invoice OCR solutions using Azure AI Document Intelligence, Azure Databricks, Azure Machine Learning, MLflow, Azure AI Search, OpenAI/GenAI, Python, and SQL, driving 98-99%+ extraction accuracy across complex supply-chain and procurement documents through advanced machine learning, document classification, validation frameworks, and intelligent automation.
Roles and Responsibilities:
Analyse invoice and contract variations across suppliers, countries, languages, formats, and scan-quality levels. Define the document taxonomy and extraction schema for: Invoice headers Contract metadata Purchase-order references
Supplier and customer information Dates, currencies, taxes, discounts, and totals Payment terms, renewal dates, obligations, and termination clauses Tables and invoice line items
Evaluate Azure AI Document Intelligence prebuilt invoice, layout, custom neural, custom template, classification, and composed-model capabilities.
Build and train custom document classifiers and extraction models. Prepare, label, clean, balance, and version training and evaluation datasets.
Implement document preprocessing for rotation, skew, noise, resolution, page separation, and scan-quality issues.
Develop confidence-scoring and validation strategies using field-level and OCR-level confidence signals. Implement deterministic validation rules, including Subtotal, tax, and total reconciliation Currency and date validation Purchase-order and supplier matching Duplicate-document detection
Required-field and cross-field consistency checks Establish confidence thresholds and human-review rules for uncertain extractions. Perform error analysis by document type, supplier, field, language, and scan quality.
Create automated evaluation pipelines reporting exact-match accuracy, precision, recall, F1 score, false-positive rates, and false-negative rates.
Monitor model drift and retrain models when document formats or business requirements change. Document model versions, training data, experiments, limitations, and release decisions. Collaborate with supply-chain, procurement, accounts-payable, legal, and engineering teams.
Experience: -Min 10+ Years
Location: - Irving, TX (Hybrid 3 days' Work from Office)
Educational Qualifications: -
Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
Technical certification in multiple technologies is desirable.
Skills: -
Mandatory skills
Min 4+ years of experience in machine learning, OCR, computer vision, NLP, or intelligent document processing. Hands-on experience with Azure AI Document Intelligence or a comparable enterprise document-processing platform.
Strong Python development skills. Experience with REST APIs, JSON, Azure SDKs, and asynchronous processing. Experience training and evaluating document classification and field-extraction models. Strong understanding of accuracy, precision, recall, F1 score, confidence calibration, and test-set design.
Experience extracting complex tables and variable-length line items. Experience creating labelled datasets and maintaining data-quality standards. Familiarity with invoices, purchase orders, contracts, or supply-chain documents.
Strong analytical, debugging, and technical-documentation skills. Preferred Qualifications Experience with Azure Machine Learning, MLflow, Azure AI Search, or Azure OpenAI. Experience with multilingual documents.
Familiarity with contract clause extraction and legal-document processing. Knowledge of ERP or procurement systems such as SAP, Oracle, Dynamics 365, Coupa, or Ariba. Experience implementing active learning, model-drift monitoring, and human-in-the-loop workflows. Knowledge of data privacy and document-retention requirements.
Success Measures 99% exact-match accuracy for approved critical fields. 98% exact-match accuracy across all agreed fields. Accuracy maintained across suppliers, formats, and document-quality categories.
Measurable reduction in manual corrections and review time. Documented improvement process for fields that miss their thresholds. No production model deployed without passing the approved evaluation suite.
Skills
Azure (Bigdata Azure) Azure AI Document Intelligence, Azure Databricks, OpenAI, GenAI, Azure Machine Learning, MLflow, Azure AI Search SQL, Contract and Invoice OCR
VeeRteq Solutions is an Equal Opportunity Employer
Role: Senior Azure AI Document Intelligence Engineer (OCR Experience)
We are seeking a Senior Azure AI Document Intelligence Engineer responsible for designing, training, and optimizing AI-powered contract and invoice OCR solutions using Azure AI Document Intelligence, Azure Databricks, Azure Machine Learning, MLflow, Azure AI Search, OpenAI/GenAI, Python, and SQL, driving 98-99%+ extraction accuracy across complex supply-chain and procurement documents through advanced machine learning, document classification, validation frameworks, and intelligent automation.
Roles and Responsibilities:
Analyse invoice and contract variations across suppliers, countries, languages, formats, and scan-quality levels. Define the document taxonomy and extraction schema for: Invoice headers Contract metadata Purchase-order references
Supplier and customer information Dates, currencies, taxes, discounts, and totals Payment terms, renewal dates, obligations, and termination clauses Tables and invoice line items
Evaluate Azure AI Document Intelligence prebuilt invoice, layout, custom neural, custom template, classification, and composed-model capabilities.
Build and train custom document classifiers and extraction models. Prepare, label, clean, balance, and version training and evaluation datasets.
Implement document preprocessing for rotation, skew, noise, resolution, page separation, and scan-quality issues.
Develop confidence-scoring and validation strategies using field-level and OCR-level confidence signals. Implement deterministic validation rules, including Subtotal, tax, and total reconciliation Currency and date validation Purchase-order and supplier matching Duplicate-document detection
Required-field and cross-field consistency checks Establish confidence thresholds and human-review rules for uncertain extractions. Perform error analysis by document type, supplier, field, language, and scan quality.
Create automated evaluation pipelines reporting exact-match accuracy, precision, recall, F1 score, false-positive rates, and false-negative rates.
Monitor model drift and retrain models when document formats or business requirements change. Document model versions, training data, experiments, limitations, and release decisions. Collaborate with supply-chain, procurement, accounts-payable, legal, and engineering teams.
Experience: -Min 10+ Years
Location: - Irving, TX (Hybrid 3 days' Work from Office)
Educational Qualifications: -
Engineering Degree BE/ME/BTech/MTech/BSc/MSc.
Technical certification in multiple technologies is desirable.
Skills: -
Mandatory skills
Min 4+ years of experience in machine learning, OCR, computer vision, NLP, or intelligent document processing. Hands-on experience with Azure AI Document Intelligence or a comparable enterprise document-processing platform.
Strong Python development skills. Experience with REST APIs, JSON, Azure SDKs, and asynchronous processing. Experience training and evaluating document classification and field-extraction models. Strong understanding of accuracy, precision, recall, F1 score, confidence calibration, and test-set design.
Experience extracting complex tables and variable-length line items. Experience creating labelled datasets and maintaining data-quality standards. Familiarity with invoices, purchase orders, contracts, or supply-chain documents.
Strong analytical, debugging, and technical-documentation skills. Preferred Qualifications Experience with Azure Machine Learning, MLflow, Azure AI Search, or Azure OpenAI. Experience with multilingual documents.
Familiarity with contract clause extraction and legal-document processing. Knowledge of ERP or procurement systems such as SAP, Oracle, Dynamics 365, Coupa, or Ariba. Experience implementing active learning, model-drift monitoring, and human-in-the-loop workflows. Knowledge of data privacy and document-retention requirements.
Success Measures 99% exact-match accuracy for approved critical fields. 98% exact-match accuracy across all agreed fields. Accuracy maintained across suppliers, formats, and document-quality categories.
Measurable reduction in manual corrections and review time. Documented improvement process for fields that miss their thresholds. No production model deployed without passing the approved evaluation suite.
Skills
Azure (Bigdata Azure) Azure AI Document Intelligence, Azure Databricks, OpenAI, GenAI, Azure Machine Learning, MLflow, Azure AI Search SQL, Contract and Invoice OCR
VeeRteq Solutions is an Equal Opportunity Employer
See All 351+ AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
Find AI Engineer JobsAI Engineer Jobs by City in Texas
Where Texas roles are concentrated, by current openings.
AI Engineer Job Market in Texas
A snapshot from current Texas openings, updated as new roles post.
Who's Hiring
- SpaceX23
- AMD15
- JPMorganChase10
- TeamViewer8
- Apple6
Top Industries Hiring
- Technology & Software19
- Consulting & Professional Services12
- Electronics & Hardware8
- Law & Legal Services4
- Food & Beverage3
What Texas Employers Look For
The qualifications that appear most often in AI engineer jobs across Texas.
- Bachelor's or master's degree in computer science, data science, or a related engineering field
- Hands-on experience building and deploying machine learning models in production environments
- Proficiency in Python and familiarity with frameworks such as TensorFlow, PyTorch, or JAX
- Experience with cloud platforms including AWS, Azure, or Google Cloud for model hosting
- Strong understanding of MLOps practices including CI/CD pipelines and model monitoring
- Ability to collaborate with cross-functional teams including data engineers and product managers
AI Engineer Jobs in Texas: Frequently Asked Questions
How do you become a ai engineer in Texas?
Texas does not require a state-issued license to work as an ai engineer, so the path runs through education and demonstrated technical skills. Most Texas employers expect at minimum a bachelor's degree in computer science, data science, or electrical engineering, with a master's degree competitive at larger companies like Dell, Boeing, or the major energy firms. Building a portfolio of deployed model projects and earning cloud certifications from AWS or Google strengthens applications considerably.
Which companies hire ai engineers in Texas?
Employers hiring ai engineers in Texas right now include SpaceX, AMD, and JPMorganChase, based on current listings on Migrate Mate as of September 2026. Texas's concentration of defense contractors, energy majors, and large enterprise technology campuses means ai engineer openings appear across a wider range of industries than most states.
Which Texas cities have the most ai engineer jobs?
Austin, Dallas, and Plano hold the most ai engineer openings in Texas. Austin's dense technology startup and corporate campus ecosystem drives the bulk of software-focused roles, Dallas anchors financial services and telecom AI hiring, and Houston's energy sector generates strong demand for ai engineers working on industrial automation and predictive maintenance applications.
Are there remote ai engineer jobs in Texas?
Yes, and more than most fields, since ai engineering work is largely code, experimentation, and model evaluation that transfers well to remote environments. About 74% of ai engineer openings tied to Texas are remote or hybrid as of September 2026, reflecting how broadly distributed this talent pool has become. Roles focused on research, NLP, and model fine-tuning tend to be the most remote-accessible, while positions involving on-premise GPU infrastructure or classified defense work are typically on-site.
How can I get hired as a ai engineer in Texas with little or no experience?
The most realistic entry path is through a machine learning engineering or data science associate role, which several large Texas employers use as a structured on-ramp. Companies like Texas Instruments and Raytheon run rotational engineering programs that include AI and data tracks, and energy firms including Chevron and ExxonMobil hire data science associates at Texas campuses. Building two or three end-to-end project deployments on GitHub, earning an AWS or Google Cloud machine learning certification, and targeting these associate-level postings gives candidates without prior industry experience a credible foundation.
Where can I find and apply to ai engineer jobs in Texas?
You can find and apply to ai engineer jobs in Texas on Migrate Mate, which lists current Texas openings from employers actively hiring in the state. Find the roles that fit your background and apply directly through each listing.
See All 351+ AI Engineer Jobs in Texas
Find roles in Texas that match your experience and apply in just a few clicks.
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