AI/ML Engineer

Carter Support ServicesBurbank, CA
Onsite

About The Position

Carter Support Services is seeking a highly experienced Senior AI/ML Engineer to design, develop, and deploy advanced AI solutions. This role focuses on building scalable systems leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and agentic AI workflows. The ideal candidate will bring deep expertise in Python, cloud-based AI deployment (Azure), and modern NLP techniques, along with experience delivering production-grade AI systems.

Requirements

  • Bachelor’s degree in Computer Science, Engineering, or related field
  • 10+ years of experience in software engineering or AI/ML roles
  • 7+ years of Python experience (expert-level proficiency required)
  • 7+ years of Microsoft Azure experience, including Azure Machine Learning
  • 7+ years of DevOps experience, including CI/CD pipelines
  • 7+ years of MongoDB or similar database experience
  • Strong experience with LLM integration and RAG architectures
  • Experience with prompt engineering and context optimization
  • Solid understanding of NLP and transformer-based models
  • Experience with vector databases and search systems
  • Familiarity with agentic AI workflows and tool/function calling

Nice To Haves

  • Experience with Azure OpenAI API
  • Experience building scalable, enterprise-grade AI applications
  • Background in AI system monitoring, evaluation, and optimization

Responsibilities

  • Design and implement AI/ML solutions using Python and modern ML frameworks
  • Develop and optimize prompt engineering strategies for LLM-based systems
  • Build and deploy RAG (Retrieval-Augmented Generation) pipelines
  • Integrate LLMs via APIs (Azure OpenAI preferred) into enterprise applications
  • Develop and orchestrate agentic AI workflows with tool/function calling
  • Implement vector search solutions using vector databases or MongoDB
  • Ensure CI/CD integration and cloud deployment (Azure preferred)
  • Establish observability, monitoring, and evaluation frameworks for AI systems
  • Collaborate cross-functionally to deliver production-ready AI features
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