1

Huggingface Jobs in Texas (NOW HIRING)

LLM Infrastructure Engineer

Houston, TX · On-site

$97K - $127K/yr

Build and deploy LLM inference services using HuggingFace Transformers and PyTorch * Optimize GPU workloads and CUDA memory usage * Implement streaming inference APIs for real-time model responses

PyTorch, TensorFlow, HuggingFace, LangChain. * Evaluation/annotation tools: Scale AI, GroundTruth, Labelbox, Prodigy. * Prompt testing tools: Weights & Biases, MLflow, OpenAI evals, LLM-as-a-judge ...

Experience with OpenAI APIs , Azure OpenAI, HuggingFace, and prompt engineering. * Familiarity with building scalable APIs using FastAPI , Flask, or Django. * Handson knowledge of cloud services ...

Sr Data Scientist GenAI

Dallas, TX · On-site

$150K - $210K/yr

... HuggingFace etc. - Proven track record building transformer/NLP / LLM models; experience with fine-tuning, prompt engineering. - Solid experience with information retrieval / search: keyword ...

Gen AI Lead

Dallas, TX · On-site

$138K - $170K/yr

... HuggingFace * Tools/Framework: Git, TensorFlow, PyTorch, PySpark, AWS, MLflow, Docker, Kubernetes, Databricks, SparkSQL, OpenCV, Azure, YOLO, Scikit-Learn, FastAPI, Flask, Django, Keras, Pandas ...

... Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. • Invent and introduce state-of-the-art LLM optimization techniques to improve the performance -- scalability, cost, latency, throughput ...

Sr Data Scientist GenAI

Dallas, TX · On-site +1

$150K - $210K/yr

... HuggingFace etc. - Proven track record building transformer/NLP / LLM models; experience with fine-tuning, prompt engineering. - Solid experience with information retrieval / search: keyword ...

Position requires: 1. Deep Learning, Generative AI, LLM; 2. Python, C and C++; 3. Dataset design and curation at scale, and Synthetic data generation; 4. OpenCV, Git, and HuggingFace; 5. PyTorch ...

Lead Software Engineer

Dallas, TX · On-site

$92K - $170K/yr

Leverage a broad stack of Open Source and SaaS AI technologies such as AWS Ultraclusters, Huggingface, VectorDBs, Nemo Guardrails, PyTorch, and more. * Invent and introduce state-of-the-art LLM ...

next page

Showing results 1-20

Huggingface information

What are the key skills and qualifications needed to thrive in the Huggingface position, and why are they important?

To thrive in a role at Hugging Face, you typically need strong skills in machine learning, natural language processing (NLP), and software development, supported by a relevant degree in computer science or a related field. Familiarity with frameworks like PyTorch or TensorFlow, plus experience using version control systems such as Git, are often required; open-source contributions and cloud platform knowledge are a plus. Excellent communication, collaborative teamwork, and problem-solving abilities help candidates stand out in this dynamic, innovation-driven environment. These strengths are crucial because they enable individuals to develop high-impact AI tools, work effectively in interdisciplinary teams, and contribute to open-source communities.

What does a typical day look like for an engineer working at Hugging Face?

As an engineer at Hugging Face, your day typically involves collaborating with team members to design, develop, and improve state-of-the-art machine learning models and tools, with a strong focus on open-source NLP projects. You’ll participate in code reviews, experiment with new technologies, engage with the community through forums or GitHub, and help support user questions or issues. Expect a fast-paced, collaborative environment where cross-functional teamwork with product managers, researchers, and other engineers is common. The work is project-driven, with plenty of opportunities to contribute ideas, learn from experts, and advance your technical skills.

What is a Huggingface job?

A Hugging Face job typically refers to a role at Hugging Face, a company specializing in machine learning and natural language processing (NLP). Employees at Hugging Face work on developing and maintaining open-source AI tools, including the popular Transformers library. Roles range from research and engineering to product and community development, often focusing on advancing state-of-the-art AI models.

What are the most commonly searched types of Huggingface jobs in Texas? The most popular types of Huggingface jobs in Texas are:
What job categories do people searching Huggingface jobs in Texas look for? The top searched job categories for Huggingface jobs in Texas are:
Infographic showing various Huggingface job openings in Texas as of July 2026, with employment types broken down into 1% Internship, 97% Full Time, and 2% Part Time. Highlights an 86% Physical, 1% Hybrid, and 13% Remote job distribution.

LLM Infrastructure Engineer

AMSYS Talent

Houston, TX • On-site

$97K - $127K/yr

Full-time

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

We are looking for a Senior Python / AI API Engineer to build and deploy production-grade services powering Large Language Model (LLM) applications. This role focuses on developing high-performance APIs for model inference, optimizing GPU workloads, and deploying AI services in cloud environments.
This is an engineering-focused role, not research. We are looking for someone who has built and shipped AI systems into production and understands the challenges of scalable inference and model serving.
Key Responsibilities
  • Develop high-performance APIs using Python (3.10+) and FastAPI
  • Build and deploy LLM inference services using HuggingFace Transformers and PyTorch
  • Optimize GPU workloads and CUDA memory usage
  • Implement streaming inference APIs for real-time model responses
  • Containerize and deploy services using Docker and GPU-enabled infrastructure
  • Deploy AI workloads in Azure environments (AKS, ACI, or Container Apps)

Required Skills
  • Strong Python development experience (3.10+)
  • Hands-on experience building production APIs with FastAPI
  • Experience with HuggingFace Transformers and PyTorch
  • Solid understanding of REST API design
  • Experience deploying containerized applications with Docker

Nice to Have
  • Experience with OpenAI-compatible APIs, vLLM, or Text Generation Inference (TGI)
  • Experience deploying AI workloads on Azure GPU infrastructure
  • Familiarity with LoRA / PEFT fine-tuning
  • Exposure to legal or financial NLP use cases

Ideal Candidate: A hands-on engineer who understands how LLM systems run in production-from model loading and tokenization to GPU deployment and scalable APIs.