Engineer/ Sr Engineer/ Lead Sr Engi...

Role Overview

This position is within Qualcomm India Private Limited (Qualcomm), located in Bengaluru. We are seeking a talented engineer to build scalable cloud-native AI applications that enhance engineering productivity for our chip design teams.

About the Team

The team focuses on applying advanced AI/ML and GenAI technologies to solve complex business problems in chip design, qualification, and debug engineering processes. Our goal is to enhance engineering efficiency through intelligent automation, data-driven insights, and innovative tool development.

Key Responsibilities

• Design and implement robust AI/ML applications and pipelines using LLMs, GenAI platforms (e.g., LangChain), RAG optimization, and custom models tailored to real-world engineering challenges in chip design and debug workflows.
• Build intelligent agents and intuitive user interfaces that integrate seamlessly into daily engineering operations.
• Develop scalable data ingestion, transformation, and analysis pipelines capable of handling large datasets using SQL/NoSQL databases and ETL frameworks.
• Create and maintain distributed computing architectures and backend services on cloud platforms (AWS) to support big data analytics needs.
• Collaborate with cross-functional teams including hardware engineers, product managers, and QA specialists to deliver high-quality solutions.

Minimum Qualifications

• Bachelor's degree in Computer Science, Electrical/Electronics Engineering, or a related field. Preferred: Master's or PhD.
• Very strong foundation in data structures, algorithms, and software design principles.
• Demonstrated proficiency in Python (with libraries like Pandas, NumPy) and C/C++.
• Experience building scalable software systems to solve complex technical problems independently.
• Strong analytical skills with the ability to learn new technologies quickly.

Preferred Qualifications

• Familiarity with cloud platforms (AWS), ETL frameworks, and SQL databases.
• Hands-on experience in Cloud Scale & Distributed Computing Architectures.
• In-depth knowledge of AI/ML including Supervised/Upsupervised learning, PyTorch/TensorFlow/scikit-learn.