ZipRecruiter

Log In

1

Hugging Face Jobs in Austin, TX (NOW HIRING)

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

... Hugging Face Transformers for model development, fine-tuning, and optimization. • Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific ...

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

... Hugging Face Transformers for model development, fine-tuning, and optimization. • Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific ...

webAI

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

... Hugging Face Transformers for model development, fine-tuning, and optimization. • Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific ...

smart folks inc

IAM FullStack developer

Austin, TX · On-site

Proven track record building GenAI solutions using RAG : embeddings, vector search, retrieval tuning, prompt engineering, LLM integrations (OpenAI/Azure OpenAI/Anthropic/Hugging Face), using ...

webAI Inc

Senior Machine Learning Engineer

Austin, TX · On-site

$103K - $142K/yr

Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers. * Proven experience deploying AI models across cloud, edge, and mobile hardware environments. * Expertise in model compression ...

TSMC

Senior AI Model Fine-Tuning Engineer

Austin, TX · On-site

$103K - $142K/yr

... Hugging Face, TensorFlow, or PyTorch. • Deep understanding of LLM behaviors, including instruction-following, task completion, and ethical considerations in output. • Proficiency in Python and ...

Donato Technologies, Inc

AI/ML Engineer

Austin, TX · On-site

... Hugging Face, Azure AI) 4 Required Experience integrating LLMs via APIs Knowledge of AI governance, model lifecycle management, and evaluation 4 Required Experience implementing and extending the ...

SpangleAI

AI/ML Scientist

Austin, TX · On-site

... Hugging Face, and libraries focused on GAI/LLM development • Familiarity with data warehouse and data pipeline technologies (e.g., Amazon Redshift, Google BigQuery, Snowflake, Apache Airflow) • ...

Apple

Formal Verification - AI/ML Engineer

Austin, TX · On-site

$134K/yr

Proficiency in Python and modern ML/AI frameworks and tooling (e.g., PyTorch, LangChain, LlamaIndex, Hugging Face, or similar). Background in formal methods, mathematical logic, or a strong ...

Arrive Logistics

Data Scientist II

Austin, TX · On-site

... with Hugging Face Transformers for text classification or related NLP tasks. • Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including ...

Seekr

Forward Deployed Engineer

Austin, TX

Hands-on expertise with AI/ML and LLM frameworks (e.g., PyTorch, Hugging Face, LangChain, vLLM), including model fine-tuning and agent deployment. * Proven experience designing, deploying, and ...

ForeFlight

Staff Machine Learning Engineer

Austin, TX · On-site +1

$208K - $255K/yr

Familiarity with NVIDIA NeMo, Kaldi, ESPnet, Hugging Face, Whisper, DeepSpeed, or equivalent ecosystems. * Strong Python engineering skills and experience building production ML systems. * Experience ...

Sourceability

Principal NLP Scientist

Austin, TX

Strong experience with PyTorch and Hugging Face Transformers * Experience with ONNX or other model optimization / model serving formats * Strong understanding of data preparation, data quality ...

next page

Showing results 1-20

All JobsHugging Face JobsHugging Face Jobs in Austin, TX

Hugging Face information

See Austin, TX salary details

$8

$14

$19

How much do hugging face jobs pay per hour?

As of Aug 10, 2026, the average hourly pay for hugging face in Austin, TX is $14.61, according to ZipRecruiter salary data. Most workers in this role earn between $12.26 and $17.26 per hour, depending on experience, location, and employer.

What is the difference between Hugging Face vs Machine Learning Engineer?

AspectHugging FaceMachine Learning Engineer
Required CredentialsTypically requires knowledge of NLP, deep learning, and Python; certifications are optionalRequires degrees in CS or related fields; experience with ML frameworks; certifications beneficial
Work EnvironmentCollaborative, research-focused, often in tech companies or startupsDevelopment, deployment, and optimization of ML models in various industries
Employer & Industry UsageUsed by AI/ML companies, research labs, and open-source communitiesEmployed across tech, finance, healthcare, and other sectors implementing ML solutions

Hugging Face primarily focuses on NLP tools, libraries, and open-source models, serving as a platform for AI research and development. Machine Learning Engineers develop, implement, and optimize ML models across various domains. While Hugging Face offers resources and tools that ML Engineers use, the roles differ: Hugging Face is a platform, whereas Machine Learning Engineer is a job role involving hands-on model development and deployment.

What are popular job titles related to Hugging Face jobs in Austin, TX? For Hugging Face jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Hugging Face jobs in Austin, TX look for? The top searched job categories for Hugging Face jobs in Austin, TX are:
What cities near Austin, TX are hiring for Hugging Face jobs? Cities near Austin, TX with the most Hugging Face job openings:
Hugging Face jobs near you
Infographic showing various Hugging Face job openings in Austin, TX as of August 2026, with employment types broken down into 77% Full Time, 20% Part Time, and 3% Contract. Highlights an 92% Physical, 1% Hybrid, and 7% Remote job distribution, with an average salary of $30,398 per year, or $14.6 per hour.

Senior Machine Learning Engineer

webAI

Austin, TX • On-site

$103K - $142K/yr

Full-time

Re-posted 22 days ago

Job description

Job Summary:
webAI is seeking a Senior Machine Learning Engineer to support their Public Sector initiatives focused on building and optimizing production-ready AI systems. The role involves transforming prototype models into scalable and reliable production systems that operate across various hardware environments.
Responsibilities:
• Design, develop, and deploy agentic workflows to orchestrate multi-step reasoning, tool use, and decision-making across production systems.
• Productionize AI models from research prototypes into scalable, deployable systems used in real world applications.
• Engineer adaptive ML systems using LoRA, PEFT, and on-device inference strategies, leveraging PyTorch, TensorFlow, and Hugging Face Transformers for model development, fine-tuning, and optimization.
• Implement model optimization techniques such as quantization, pruning, distillation, and hardware specific acceleration.
• Build and maintain Retrieval Augmented Generation (RAG) pipelines, including vector database integration for contextual retrieval.
• Work with multi-modal AI systems across computer vision, audio, and natural language domains.
• Optimize model execution for distributed and resource constrained environments, ensuring reliability under variable connectivity conditions.
Qualifications:
Required:
• Active US Security clearance
• 4+ years of experience in applied AI, ML engineering, or production AI systems.
• Deep proficiency in PyTorch, TensorFlow, or Hugging Face Transformers.
• Proven experience deploying AI models across cloud, edge, and mobile hardware environments.
• Expertise in model compression and optimization (quantization, pruning, distillation).
• Experience building RAG pipelines and integrating vector databases (e.g., Quadrant, ChromaDB, FAISS, Milvus, Pinecone).
• Familiarity with multi-modal models and synthetic data generation methods.
• Strong algorithmic and problem solving skills, especially in distributed or constrained compute environments.
Preferred:
• Experience with edge AI, federated learning, or offline inference systems.
• Understanding of AI governance and compliance frameworks relevant to public sector deployments.
• Experience integrating models into large scale distributed systems or microservice architectures.
• Excellent communication and technical documentation skills for collaboration across multi disciplinary teams.
• Strong understanding of GPU computing, CUDA, and performance profiling.
Company:
The leader in private AI. Founded in 2020, the company is headquartered in Austin, USA, with a team of 51-200 employees. The company is currently Growth Stage.

Apply