Generative AI Engineer: LLMs, RAG & Agent Systems

Qualcomm Incorporated; San Diego (CA); On-site; USD 115,000 - 172,000; Full time

Job summary

Qualcomm Technologies, Inc. is seeking an experienced Machine Learning Engineer specializing in Generative AI to join our core AI team in San Diego.

You will design, develop, and deploy cutting-edge generative AI solutions focusing on Large Language Models, Retrieval-Augmented Generation, and intelligent agent systems. The role involves designing RAG-based enhancements, fine-tuning strategies, evaluation frameworks, and autonomous agent workflows, collaborating with cross-functional teams to

Qualifications

• Bachelor's degree in CS/CE/EE or related field.
• Experience with popular LLM frameworks (Langchain, LlamaIndex, Transformers).
• Knowledge of prompt engineering and chain-of-thought techniques.
• Experience with containerization and microservices architecture.
• Background in reinforcement learning.
• Contributions to open-source AI projects.
• Experience with ML ops and model deployment pipelines.

Responsibilities

• Design and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources.
• Develop and optimize LLM fine-tuning strategies for specific use cases and domain adaptation.
• Create robust evaluation frameworks for measuring and improving model performance.
• Build and maintain agentic workflows for autonomous AI systems.
• Collaborate with cross-functional teams to identify opportunities and implement AI solutions.

Skills

Python

ML Frameworks

LLM Deployments

Vector Databases

RAG Architectures

PyTorch

TensorFlow

Education

Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, or related field

Tools

Langchain

LlamaIndex

Transformers

Docker

Kubernetes

Job description

Qualcomm Technologies, Inc. is seeking an experienced Machine Learning Engineer specializing in Generative AI to join our core AI team in San Diego.

You will design, develop, and deploy cutting-edge generative AI solutions focusing on Large Language Models, Retrieval-Augmented Generation, and intelligent agent systems. The role involves designing RAG-based enhancements, fine-tuning strategies, evaluation frameworks, and autonomous agent workflows, collaborating with cross-functional teams to