Compare your current skills to what this opportunity needs—we'll show you what you already have and what could strengthen your application.
Job Description
Job Title :
Senior ML/AI Engineer Location :
Charlotte NC [5 days onsite] This role is critical for designing, developing, and optimizing the core AI and RAG components of the system.
Key Skills & Responsibilities Gen AI:
Deep understanding of generative AI models, LLMs, and their application in conversational interfaces. Experience with fine-tuning or adapting models for specific tasks.
LangGraph:
Expertise in building agentic systems and state machines using LangGraph. Understanding of agent orchestration, managing conversational flow, and integrating various tools/models.
Python:
Strong proficiency in Python, including experience with relevant AI/ML libraries (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face).
RAG Implementation:
Experience in designing and implementing Retrieval Augmented Generation systems, including vector databases, embedding techniques, and efficient retrieval strategies. Cloud Platform (Google Cloud): Experience deploying and managing AI/ML workloads on Google Cloud Platform (Google Cloud Platform) has added advantage. Familiarity with relevant services like Vertex AI, Cloud Functions, Cloud Run, or GKE for model deployment.
Async Programming:
Have understanding or ability to write efficient asynchronous code for handling potentially long-running AI model calls and external API interactions.
REST:
Understanding of RESTful principles for integrating AI services with other parts of the system.
Logging:
Experience with implementing robust logging for monitoring AI model performance, identifying issues, and tracking usage. Familiarity with tools like Splunk is a plus