Senior ML Engineer — Generative AI & LLMs

Latitude; San Diego (CA); On-site; USD 135,000 - 203,000; Full time

Job summary

Qualcomm Technologies, Inc. in San Diego, CA is seeking an experienced Machine Learning Engineer specializing in Generative AI to design, develop, and deploy cutting-edge generative AI solutions, with a focus on LLMs, Retrieval-Augmented Generation (RAG), and intelligent agent systems.

You will design and implement RAG-based knowledge integration, develop LLM fine-tuning strategies for domain adaptation, create robust evaluation frameworks, and build cross-functional, end-to-end AI workflows.

Qualifications

• 3+ years of experience in Machine Learning/AI engineering
• Strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow)
• Practical experience with LLM deployments and fine-tuning
• Experience with vector databases and embedding models
• Familiarity with cloud platforms (AWS, GCP, Azure) and ML ops

Responsibilities

• Design and implement RAG-based solutions to enhance LLM capabilities with external knowledge sources
• Develop and optimize LLM fine-tuning strategies for 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

Problem-solving

Analytical thinking

Communication

Collaboration

Agile development

Code quality

AI ethics

Education

Bachelor's/Master's/PhD in CS/EE

Tools

Langchain

LlamaIndex

Transformers

PyTorch

TensorFlow

Docker

Kubernetes

Job description

Qualcomm Technologies, Inc. in San Diego, CA is seeking an experienced Machine Learning Engineer specializing in Generative AI to design, develop, and deploy cutting-edge generative AI solutions, with a focus on LLMs, Retrieval-Augmented Generation (RAG), and intelligent agent systems.

You will design and implement RAG-based knowledge integration, develop LLM fine-tuning strategies for domain adaptation, create robust evaluation frameworks, and build cross-functional, end-to-end AI workflows.