AI Engineer

Looking for AI Engineer for Remote or Onsite in Houston, Texas

Must have Master's or PHD in Computer Science or Related Field

Must be able to share 2 Managerial References at the time of submission

Job Description -

Must be computer vision expert, LinkedIn Must, 2 manager reference

Master s or Ph.D. in Computer Science or a related field (Ph.D. preferred)

Job Title: AI Engineer - LLM Development Project

Worksite: Full Remote Available, or Houston TX Onsite Mon-Thur

We are seeking a skilled AI Engineer with a strong background in Large Language Models (LLMs), a deep understanding of AI concepts, and hands-on experience with the LLM framework. As a member of our team, you will play a pivotal role in designing, developing, and deploying agent-based AI solutions. This role requires leveraging cutting-edge tools and methodologies to enhance performance, accuracy, and scalability, with a particular focus on AI deployment and scaling best practices.

Master s or Ph.D. in Computer Science or a related field. The ideal candidate has strong experience in deep learning (PyTorch/TensorFlow), computer vision (CNNs, Vision Transformers) and/or large language models (GPT, DeepSeek, etc.). Proficiency in Python, ML pipelines, and cloud platforms is essential. Familiarity with multi-agent systems or reinforcement learning is a plus. Experience deploying models using AWS, CDK, and Docker is required.

Key Responsibilities:

Agent-Based Application Development: Develop intelligent, autonomous agents capable of handling complex tasks within AI applications to drive performance and user satisfaction.

Prompt Engineering: Design and optimize prompt structures to improve the accuracy and relevance of AI outputs, ensuring robust interactions with LLMs.

LLM Framework Implementation: Implement and fine-tune large language models, utilizing frameworks for optimal response generation, efficiency, and scalability.

AI Deployment & Scaling: Oversee the deployment and scaling of LLMs in production environments, ensuring effective resource use and high performance under varying workloads.

Requirements:

LLM Framework Expertise: Proven experience with large language model frameworks, including deployment, fine-tuning, and inference techniques.

Machine Learning Background: Strong foundation in machine learning principles, particularly as applied to LLMs and agent-based architectures.

Programming Skills: Proficiency in Python and familiarity with essential AI libraries (e.g., PyTorch, Langchain/Langgraph, Bedrock).

Deployment and Scalability: Familiarity with deploying and scaling AI solutions in production environments to ensure reliability and efficiency.

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