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Face Models Jobs in Texas (NOW HIRING)

Vytwo

Lead AI Engineer - Bengaluru, INDIA

Prosper, TX · On-site

$93K - $123K/yr

Fine-tune LLMs using LoRA/QLoRA and integrate with Azure OpenAI or Hugging Face models. * Implement vector search and retrieval pipelines using FAISS or Azure Cognitive Search. * Ensure responsible ...

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Face Models information

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$9

$42

$132

How much do face models jobs pay per hour?

As of Aug 16, 2026, the average hourly pay for face models in Texas is $42.59, according to ZipRecruiter salary data. Most workers in this role earn between $13.89 and $67.16 per hour, depending on experience, location, and employer.

What is the difference between Face Models vs Makeup Models?

AspectFace ModelsMakeup Models
Required CredentialsMinimal; often based on appearance and skin conditionMinimal; focus on makeup application and skin suitability
Work EnvironmentPhoto shoots, fashion shows, advertisingPhoto shoots, beauty campaigns, runway shows
Industry UsageFashion, advertising, beautyBeauty, cosmetics, fashion
Search & Comparison IntentPeople seeking face modeling opportunities or infoPeople comparing face models and makeup models roles

Face models primarily focus on showcasing facial features for various media, requiring minimal credentials. Makeup models, on the other hand, are used to display makeup products and techniques. Both roles are common in fashion and beauty industries, often overlapping in photo shoots and campaigns. Understanding these differences helps individuals identify the right modeling path based on their appearance and career goals.

What are the requirements for a face model?

Face models typically need clear, symmetrical facial features, good skin condition, and a versatile appearance to suit various projects. No formal education is required, but a professional portfolio or headshots are often necessary to demonstrate suitability. Physical fitness and the ability to follow directions are also important for fitting and photo sessions.

How do you get into face modeling?

To become a face model, individuals typically build a portfolio with professional photographs that showcase their facial features, often working with photographers or agencies. Having clear skin, symmetrical features, and good skin care are important, and some models may need to attend casting calls or sign with a modeling agency to find opportunities.
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What are popular job titles related to Face Models jobs in Texas?

For Face Models jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Face Models jobs in Texas look for?

The top searched job categories for Face Models jobs in Texas are:

What cities in Texas are hiring for Face Models jobs?

Cities in Texas with the most Face Models job openings:

Face Models jobs near you
Infographic showing various Face Models job openings in Texas as of August 2026, with employment types broken down into 70% Full Time, and 30% Part Time. Highlights an 100% In-person job distribution, with an average salary of $88,587 per year, or $42.6 per hour.

Lead AI Engineer - Bengaluru, INDIA

Vytwo

Prosper, TX • On-site

$93K - $123K/yr

Full-time

Re-posted 18 days ago

Job description

Role: Lead AI Engineer - Bengaluru, INDIA
Full Time
*Consultants local to INDIA only
Primary Responsibilities: 
This role focuses on building production-ready AI applications and deploying them on Azure Databricks and Azure cloud infrastructure. You will work end-to-end: from data ingestion and model integration to scalable deployment, monitoring, and ongoing optimization.
The expectation is to convert AI ideas into reliable, governed, and cost-efficient applications that run in production. You will design data and AI pipelines, integrate models (including ML and Generative AI), and deploy them using Databricks workflows and Azure-native services.
Success in this role requires strong hands-on experience with Azure Databricks, Python, SQL, and Azure services, along with a clear understanding of how AI systems fail in production—and how to prevent it. You will collaborate closely with data scientists, platform engineers, and business stakeholders to ensure AI applications are usable, scalable, and maintainable beyond the first release.
 Key Responsibilities
  • Design and build end-to-end data and AI pipelines using Azure Databricks.
  • Develop robust ETL/ELT workflows using Python (PySpark) and SQL.
  • Implement CI/CD pipelines for Databricks deployments (jobs, notebooks, workflows).
  • Integrate Databricks with Azure services (Data Lake, Blob Storage, Key Vault, Azure OpenAI, Azure Functions, etc.).
  • Optimize jobs for performance, cost, and reliability.
  • Build reusable, modular code.
  • Collaborate with data scientists and platform teams to move models from experimentation to production.
  • Implement logging, monitoring, and error handling for production pipelines.
  • Develop and deploy ML and Generative AI models (LLMs, embeddings, RAG pipelines) for NLP, computer vision, and predictive analytics.
  • Fine-tune LLMs using LoRA/QLoRA and integrate with Azure OpenAI or Hugging Face models.
  • Implement vector search and retrieval pipelines using FAISS or Azure Cognitive Search.
  • Ensure responsible AI practices, including bias detection and model governance.
 Good to Have (Strong Advantage)
  • Experience with ML and Generative AI workloads on Databricks.
  • RAG, embeddings, or inference pipelines.
  • Terraform / ARM / Bicep for infrastructure.
  • Databricks Asset Bundles.
  • Airflow or ADF orchestration.
  • Production monitoring and cost optimization experience.
  • Knowledge of LangChain or similar frameworks for AI application development.
  • Experience with Azure AI services (Azure Machine Learning, Azure Cognitive Services).
 Requirements
  • Azure Databricks (jobs, workflows, clusters, Unity Catalog preferred).
  • Python (PySpark-heavy, not just pandas).
  • SQL (complex joins, window functions, analytical queries).
  • Azure Cloud (ADLS Gen2, ADF, Key Vault, IAM concepts).
  • Pipeline orchestration & deployment (CI/CD, environment promotion).
  • Azure DevOps.
  • Strong understanding of ML lifecycle and MLOps best practices.
  • Experience with model deployment using MLflow or similar frameworks.

Flexible work from home options available.