What are the responsibilities and job description for the Senior AI/ ML Engineer- Charlotte NC position at Lorven Technologies, Inc.?
Senior AI/ ML Engineer
Position: Contract
Location: Charlotte NC
Duration: 12 months
Job description:
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
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
Salary : $58 - $60