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# AI/Ml Engineer

- **Company:** Robert Half
- **Location:** Houston, TX, United States
- **Experience:** Experienced
- **Contract:** Temporary contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Software Applications, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Python (Programming Language), Machine Learning, Natural Language Processing, Open Source Technology, Tensorflow, Pytorch, Large Language Models, Generative AI, AI Platforms, Kubernetes, Information Technology, Machine Learning Operations, Databricks
- **Published:** July 19, 2026
- **Apply:** https://dejobs.org/x/x/651F61B13C3047DA9BC535DA9CCE11A2/job/

## About the Role

* Bachelor's degree in Computer Science, Data Science, Engineering, or related field.
 * 3+ years of experience in Machine Learning, AI, or Data Engineering.
 * Proficiency in Python and ML frameworks such as PyTorch, TensorFlow, LangChain, or LlamaIndex.
 * Experience with cloud platforms (Azure, AWS, or GCP) and AI services.
 * Knowledge of LLMs, NLP, vector databases, embeddings, and RAG frameworks.
 * Strong understanding of MLOps, APIs, and scalable system design.

Preferred Skills:

 * Experience fine-tuning foundation models and deploying AI solutions in production.
 * Familiarity with Azure AI Foundry, Databricks, MLflow, Kubernetes, and CI/CD pipelines.
 * Excellent problem-solving, communication, and stakeholder management skills.
Technology Doesn't Change the World, People Do.®

## Description

We are seeking an AI/ML Engineer with a focus on Generative AI to design, develop, and deploy advanced AI solutions that drive business innovation. This role will leverage large language models (LLMs), machine learning, and cloud-based AI technologies to build intelligent applications, automate workflows, and enhance data-driven decision-making., * Design, develop, and deploy Generative AI solutions using LLMs such as OpenAI, Claude, Gemini, or open-source models.

 * Build and optimize AI/ML pipelines for model training, fine-tuning, evaluation, and inference.
 * Develop Retrieval-Augmented Generation (RAG) architectures and integrate vector databases.
 * Collaborate with software engineers, data engineers, and business stakeholders to deliver AI-powered applications.
 * Implement prompt engineering strategies and model optimization techniques to improve performance and accuracy.
 * Monitor, troubleshoot, and enhance AI models in production environments.
 * Ensure AI solutions adhere to security, governance, and responsible AI best practices.


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