AI Engineer
Position Title: AI Engineer
6 month + extension
Houston, TX Hybrid (M-TH)
Job Summary
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.
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.
Position Title: AI Engineer
6 month + extension
Houston, TX Hybrid (M-TH)
Job Summary
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.
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.
