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Foundation Models Jobs in Texas (NOW HIRING)

Seekr

Senior AI Infrastructure Engineer

Austin, TX

$107K - $146K/yr

As a Senior AI Infrastructure Engineer, you will design, build, and operate the platforms that enable large-scale training, serving, evaluation, and deployment of foundation models and autonomous AI ...

Seekr

Staff AI Infrastructure Engineer

Austin, TX

$106K - $139K/yr

As a Staff AI Infrastructure Engineer, you will design, build, and operate the platforms that enable large-scale training, serving, evaluation, and deployment of foundation models and autonomous AI ...

Seekr

Staff AI Infrastructure Engineer

Austin, TX · On-site

$106K - $139K/yr

Architect and optimize high-performance inference platforms capable of serving models ranging from resource-constrained edge deployments to trillion-parameter foundation models, with a focus on ...

Seekr

Senior AI Infrastructure Engineer

Austin, TX · On-site

$107K - $146K/yr

Architect and optimize high-performance inference platforms capable of serving models ranging from resource-constrained edge deployments to trillion-parameter foundation models, with a focus on ...

Cisco

Applied AI Scientist

Houston, TX

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

Cisco

Applied AI Scientist

Dallas, TX

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

Cisco

Applied AI Scientist

Austin, TX

Contribute to the research, design, and development of large-scale foundation models for machine-generated data, with a primary focus on graph data and additional support for logs, time series ...

Hexagon AB

Lead Data Scientist

Houston, TX · On-site

Build and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and RAG architectures with vector databases for compliance document understanding * Design ...

Hexagon AB

Principal AI/ML Software Engineer

Houston, TX · On-site

$128K - $172K/yr

Key Responsibilities • Build and deploy Generative AI features using foundation models (AWS Bedrock, OpenAI, Anthropic Claude) and inference pipelines with optimization of latency and cost • ...

Cloudera

Staff Software Engineer - AI

Austin, TX · Hybrid

Experience with foundation models, prompt engineering, fine-tuning, semantic search and Retrieval-Augmented Generation (RAG) using vector databases such as Pinecone, Milvus, etc. * Experience with ...

SWBC

AI Engineer

San Antonio, TX

Build, test, and optimize AI workflows utilizing foundation models, open-source LLMs, and internally trained models. * Develop and maintain AI agents, APIs, and supporting services that enable ...

Cloudera

Staff Software Engineer - AI

Austin, TX · Hybrid

Experience with foundation models, prompt engineering, fine-tuning, semantic search and Retrieval-Augmented Generation (RAG) using vector databases such as Pinecone, Milvus, etc. * Experience with ...

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Foundation Models information

How do foundation models make money?

Foundation models make money primarily by providing AI services and solutions to businesses, such as customizing models for specific applications or licensing access to pre-trained models. Companies may also generate revenue through cloud-based deployment, consulting, and ongoing support, leveraging skills in machine learning and data management.

What does a foundation model do?

A foundation model is a large-scale machine learning model trained on diverse data that can be adapted for various tasks such as natural language processing or computer vision. It serves as a base for developing specialized applications by fine-tuning or prompting. Data scientists and AI engineers often work with these models using tools like TensorFlow or PyTorch.

What is the highest paying model job?

Senior roles in foundation model development, such as Lead AI Researcher or Machine Learning Director, tend to be the highest paying jobs in the field, often offering six-figure salaries or higher. These positions require advanced expertise in deep learning, large-scale model training, and experience with high-performance computing environments.

What are the most popular foundation models?

In the context of foundation models for AI jobs, the most popular include OpenAI's GPT series, Google's BERT and T5, Meta's LLaMA, and Facebook's RoBERTa. These models are widely used for natural language processing tasks and often require expertise in deep learning frameworks like TensorFlow or PyTorch.
What are popular job titles related to Foundation Models jobs in Texas? For Foundation Models jobs in Texas, the most frequently searched job titles are:
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What cities in Texas are hiring for Foundation Models jobs? Cities in Texas with the most Foundation Models job openings:
Foundation Models jobs near you

Postdoctoral Associate - AI for Brain Tumors

Baylor College of Medicine

Houston, TX • On-site

Full-time

Re-posted 6 days ago

Baylor College of Medicine rating

8.6

Company rating: 8.6 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

67th of 613 rated colleges and universities

Job description

Summary

The Postdoctoral Associate will develop next-generation AI models for large-scale perturbation modeling in brain tumors. The project will involve building and applying state-of-the-art machine learning approaches, including foundation models, variational autoencoders (VAEs), and transformer-based architectures, to integrate single-cell and multi-omic datasets. The goal is to decode tumor cellular heterogeneity and tumor microenvironment interactions, and to identify targetable genes, pathways, and therapeutic strategies at single-cell resolution.

Baylor College of Medicine typically follows similar to the NIH stipulated stipend guidelines for Postdoctoral Associates.

Job Duties
  • Develops and implements AI models for perturbation prediction:
    • Designs, trains, and evaluates machine learning models (e.g., transformer-based architectures, VAEs, and foundation models) to predict cellular responses to genetic and pharmacologic perturbations. This includes preprocessing large-scale single-cell and multi-omic datasets, defining model architectures, optimizing training pipelines on GPU clusters, and benchmarking against existing methods.
  • Integrate and analyze large-scale single-cell and multi-omic:
    • Processes and harmonizes scRNA-seq, scATAC-seq, and related datasets across brain tumor cohorts.
    • Performs downstream analyses such as cell state annotation, pathway enrichment, and tumor–tumor microenvironment interaction modeling to generate biologically meaningful insights.
  • Leads computational research projects and method development. 
  • Performs other job-related duties as assigned.
Minimum Qualifications
  • MD or Ph.D. in Basic Science, Health Science, or a related field.
  • No experience required.
Preferred Qualifications
  • Ph.D. in Computational Biology, Bioinformatics, Computer Science  or a related quantitative field.
  • Strong background in machine learning and statistical modeling, with experience in deep learning frameworks (e.g., PyTorch or TensorFlow). Familiarity with modern architectures such as transformers, variational autoencoders (VAEs), and foundation models is highly desirable.
  • Experience in analyzing large-scale genomics or single-cell datasets (e.g., scRNA-seq, scATAC-seq). 
  • Proficiency in Python and experience with R/Seurat or Scanpy.
  • Strong skills in writing efficient, reproducible, and well-documented code.
  • Evidence of productivity through first-author publications or preprints in computational biology, machine learning, or related fields.

Baylor College of Medicine is an Equal Opportunity/Affirmative Action/Equal Access Employer.

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