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Summer Retrieval Augmented Generation Jobs in Texas

Prophecy Technologies

AI/ML Engineer

Plano, TX · On-site

$109K - $131K/yr

Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures. * Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.

Pereview Software, LLC.

AI Engineer

Dallas, TX · On-site

$90 - $120/hr

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

ClifyX

AI Architect

Plano, TX · On-site

GPT, Claude • Prompt Engineering • RAG (Retrieval Augmented Generation) • AWS Cloud • Strong architectural and hands on GenAI expertise • Experience with enterprise automation and testing ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Pereview Software

AI Engineer

Dallas, TX · On-site

Develop and maintain Retrieval-Augmented Generation (RAG) architectures using vector databases and semantic search technologies * Create, test, and refine prompts, structured outputs, and evaluation ...

Tata Consultancy Service Limited

Architect

Plano, TX · On-site

$120K - $130K/yr

Implement RAG (Retrieval-Augmented Generation) patterns using requirements, user stories, APIs, configurations, and test repositories, leverage embeddings and vector search where applicable. Apply ...

Marencor

Gen AI/ML Solution Architect

Houston, TX · On-site

$60.25 - $79.25/hr

Develop Retrieval-Augmented Generation (RAG) pipelines for intelligent document retrieval and question-answering systems. * Implement personalized recommendation engines using cutting-edge frameworks ...

Natsoft Corporation

Sierra.ai Consultant

Dallas, TX · On-site

... Retrieval-Augmented Generation (RAG) pipelines, and Agent SDKs - Skilled in building and deploying AI/LLM systems in production environments - Familiarity with AI agents, including evaluation ...

Prolim Global

AI Architect - OT Cybersecurity

Plano, TX · On-site

Design AI-enabled solutions using technologies such as large language models, retrieval-augmented generation, semantic search, embeddings, vector databases, prompt engineering, workflow orchestration ...

Pereview Software

AI Engineer

Dallas, TX · On-site

$120 - $180/hr

In this role, you will design, build, and enhance intelligent applications thatleverageLarge Language Models (LLMs), document processing pipelines, Retrieval-Augmented Generation (RAG) architectures ...

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All JobsSummer Retrieval Augmented Generation JobsSummer Retrieval Augmented Generation Jobs in Texas

Summer Retrieval Augmented Generation information

What is a summer retrieval augmented generation role?

A Summer Retrieval Augmented Generation (RAG) role typically refers to a summer position focused on developing or improving retrieval-augmented generation systems, which are AI models that combine information retrieval with generative capabilities. In this role, you might work on integrating search algorithms with large language models, enabling systems to fetch relevant information from external sources and generate accurate, context-aware responses. These positions are often found in research labs, tech companies, or startups working on advanced AI applications, and are ideal for students or early-career professionals interested in machine learning, natural language processing, and AI research.

What are some common challenges faced when working on retrieval-augmented generation (RAG) projects during a summer internship?

During a summer internship focused on Retrieval-Augmented Generation (RAG), interns often encounter challenges such as integrating retrieval systems with generative models, managing large-scale datasets, and optimizing latency for real-time responses. Collaboration with cross-functional teams—including data engineers, research scientists, and product managers—is essential for aligning project goals and troubleshooting implementation issues. Additionally, interns may need to balance exploratory research with delivering usable prototypes within tight timeframes, which helps develop both technical and project management skills.

What are the key skills and qualifications needed to thrive as a retrieval augmented generation (RAG) engineer, and why are they important?

To thrive as a Retrieval Augmented Generation (RAG) Engineer, you need a strong background in machine learning, natural language processing, and information retrieval, typically supported by a degree in computer science or a related field. Proficiency with frameworks like PyTorch or TensorFlow, experience with vector databases (e.g., FAISS, Pinecone), and familiarity with LLM APIs are commonly required. Creative problem-solving, strong communication, and the ability to collaborate across multidisciplinary teams are essential soft skills. These competencies ensure effective development, deployment, and optimization of advanced AI systems that integrate retrieval and generative capabilities.

What are the most commonly searched types of Retrieval Augmented Generation jobs in Texas?

The most popular types of Retrieval Augmented Generation jobs in Texas are:

What cities in Texas are hiring for Summer Retrieval Augmented Generation jobs?

Cities in Texas with the most Summer Retrieval Augmented Generation job openings:

Summer Retrieval Augmented Generation jobs near you

AI/ML Engineer

Prophecy Technologies

Plano, TX • On-site

$109K - $131K/yr

Full-time

Re-posted 3 days ago

Job description


AI/ML Engineer
?? Location: Plano, TX (Hybrid)
?? Duration: Long-Term Contract
Client: EmergerTech - USLBM
Job Overview
We are seeking a highly skilled AI/ML Engineer with strong expertise in Machine Learning, Deep Learning, Generative AI, and Large Language Models (LLMs) to design, build, and deploy enterprise-scale AI solutions. The ideal candidate will have hands-on experience developing production-ready AI applications, implementing MLOps best practices, and building scalable cloud-based machine learning systems.
This role offers the opportunity to work on cutting-edge AI initiatives, including Generative AI, Retrieval-Augmented Generation (RAG), LLM fine-tuning, and intelligent enterprise applications.
Key Responsibilities
  • Design, develop, train, and deploy scalable Machine Learning and Deep Learning models for production environments.
  • Build AI-powered applications using traditional ML techniques, Generative AI, and Large Language Models (LLMs).
  • Develop and optimize data pipelines for structured and unstructured data processing.
  • Fine-tune foundation models and implement Retrieval-Augmented Generation (RAG) architectures.
  • Develop REST APIs and microservices using FastAPI, Flask, or similar frameworks to expose AI models.
  • Build, automate, and maintain MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
  • Collaborate with Data Scientists, Software Engineers, Data Engineers, and business stakeholders to deliver AI-driven solutions.
  • Optimize model accuracy, scalability, inference performance, and latency.
  • Implement AI governance, responsible AI practices, model monitoring, and security best practices.
  • Stay current with emerging AI technologies, frameworks, and industry trends.

Required Qualifications
  • Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
  • 10+ years of hands-on experience in Artificial Intelligence, Machine Learning, or Data Science.
  • Strong programming experience with Python.
  • Experience with Machine Learning frameworks including TensorFlow, PyTorch, and Scikit-learn.
  • Hands-on experience with Large Language Models (LLMs), Prompt Engineering, and Generative AI.
  • Experience implementing Retrieval-Augmented Generation (RAG) solutions.
  • Knowledge of vector databases such as Pinecone, FAISS, Chroma, or Milvus.
  • Experience with MLOps platforms such as MLflow, Kubeflow, SageMaker, or Vertex AI.
  • Experience building REST APIs using FastAPI, Flask, or similar frameworks.
  • Strong understanding of SQL and NoSQL databases.
  • Hands-on experience with Docker, Kubernetes, Git, and CI/CD pipelines.
  • Experience working with cloud platforms such as AWS, Microsoft Azure, or Google Cloud Platform.
  • Excellent analytical, communication, and problem-solving skills.

Preferred Qualifications
  • Experience with LangChain, LlamaIndex, or Semantic Kernel.
  • Experience working with Azure OpenAI, OpenAI APIs, Anthropic Claude, or Google Gemini.
  • Knowledge of distributed computing frameworks such as Apache Spark.
  • Experience with Databricks or Snowflake.
  • Familiarity with Responsible AI, AI Governance, and Model Monitoring.
  • AI/ML or Cloud certifications are a plus.

Technical Skills
  • Python
  • Machine Learning
  • Deep Learning
  • Generative AI
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Retrieval-Augmented Generation (RAG)
  • LangChain / LlamaIndex
  • TensorFlow
  • PyTorch
  • Scikit-learn
  • FastAPI / Flask
  • Docker
  • Kubernetes
  • MLflow / Kubeflow
  • SQL / NoSQL
  • Vector Databases (Pinecone, FAISS, Chroma, Milvus)
  • REST APIs
  • Git
  • CI/CD
  • AWS / Azure / Google Cloud Platform

Apply