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Python Llm Jobs in Austin, TX (NOW HIRING)

STI

Lead AI Engineer

Austin, TX · On-site

$101.60K - $133.80K/yr

Elastic Search, OpenSearch, Python, LLM, GenAI, Semantic Search, Re-Ranking, AWS, Search Engineer We are looking for an AI Engineer to modernize and enhance our existing regex/keyword-based Elastic ...

Autonomize AI

ML/LLM Engineer - Applied AI

Austin, TX · On-site

Strong Python skills and familiarity with ML/LLM frameworks (PyTorch, Transformers, LangChain, LlamaIndex, etc.) * Comfort with embeddings, vector search, retrieval pipelines, and prompt tuning

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How much do python llm jobs pay per hour?

As of May 28, 2026, the average hourly pay for python llm in Austin, TX is $58.11, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

What is a Python LLM job?

A Python LLM job involves working with Large Language Models (LLMs) using Python to develop, fine-tune, and deploy AI models. Responsibilities may include data preprocessing, prompt engineering, model optimization, and integration with applications. Professionals in this role often work with frameworks like TensorFlow, PyTorch, or Hugging Face Transformers. They may also contribute to improving model efficiency, reducing bias, and ensuring ethical AI usage.

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

To excel as a Python LLM (Large Language Model) Engineer, you need strong skills in Python programming, machine learning, and natural language processing, typically supported by a degree in computer science or a related field. Proficiency with libraries such as TensorFlow, PyTorch, Hugging Face Transformers, and experience with model deployment platforms are often essential, alongside certifications in AI or data science. Effective communication, problem-solving abilities, and collaboration are important soft skills for working in interdisciplinary teams and delivering results in dynamic environments. These skills ensure the development, fine-tuning, and deployment of advanced language models that meet both technical and business objectives.

What are some common challenges faced by Python LLM Engineers in their daily work?

Python LLM Engineers often encounter challenges related to optimizing model performance, managing large datasets, and adapting models to specific business needs. Working with large-scale language models requires balancing computational resource limitations with the need for high accuracy and efficiency. Collaboration with data scientists, product managers, and DevOps engineers is routine to ensure seamless model integration and deployment. Staying updated on the latest advancements in NLP and continuously improving models based on user feedback are also important aspects of the role.
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GenAI Application Engineer (Python & LLM Prompt Engineering)

Yantran LLC

Austin, TX • Hybrid

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Title:
GenAI Application Engineer (Python
LLM Prompt Engineering)
Location:
Austin, TX (Day 1 onsite, 3 days a week)
Salary Range: *** to 125,000/Annual
for Vendors: *** ***/hr CTC
Job Summary:
We are seeking a highly skilled and motivated GenAI Application Engineer to join our team in Austin, TX. The ideal candidate will have hands-on experience in building and deploying Generative AI applications using Python, with a strong foundation in LLM prompt engineering, RAG pipelines, and vector database integration. This role involves working closely with cross-functional teams to design, develop, and optimize AI-driven solutions that enhance user experience and operational efficiency.
Key Responsibilities:
Design and develop GenAI-powered applications using Python and modern AI frameworks.
Engineer and optimize prompts for LLMs.
Implement Retrieval-Augmented Generation (RAG) pipelines aggregating data from diverse sources such as conversation histories and product documentation
Integrate and manage vector databases for semantic search and context retrieval.
Collaborate with product managers, data scientists, and DevOps teams to deliver scalable AI solutions.
Fine-tune pre-trained LLMs for domain-specific tasks and performance improvements.
Ensure robust testing, monitoring, and documentation of AI models and pipelines.
Required Skills:
Proficiency in Python and experience with AI/ML libraries (e.g., LangChain, Hugging Face, PyTorch, TensorFlow).
Agentic AI
Strong understanding of LLMs, prompt engineering, and RAG architecture.
Experience with vector databases
Familiarity with cloud platforms
Regards, ***. "*** is an Equal Employment Opportunity employer. We promote and support a diverse workforce at all levels of the company. All qualified applicants will receive consideration for employment without regard to race, religion, color, sex, age, national origin or disability. All applicants will be evaluated solely on the basis of their ability, competence, and performance of the essential functions of their positions."

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