Senior Systems Engineer

About Qualcomm India Private Limited

Qualcomm India Private Limited is at the forefront of engineering innovation. We are part of the Engineering Group, specifically within Systems Engineering.

General Summary

Qualcomm is a company of inventors that ushered in an age of rapid acceleration in connectivity and new possibilities that will transform industries, create jobs, and enrich lives. But this is just the beginning. It takes inventive minds with diverse skills, backgrounds, and cultures to transform the potential of technology into world-changing products. This is the Invention Age - and this is where you come in.

Over the last few decades, the Wireless Systems group at Qualcomm has been instrumental in driving the mobile communication revolution which has touched every aspect of our modern life. The Wireless Research and Development (WRD) team in Bengaluru is working to advance the state of the art in the Cellular industry by developing novel technology enhancements for inclusion in the next generation 3GPP/O-RAN standards and products. You now have an opportunity of joining this team.

We are looking for an individual who is passionate about system design and can work closely with data scientists, HW, SW, and test teams to deliver end-to-end solutions. The role requires the ability to build production-grade deployment systems that bridge the gap between data science and lifecycle management of machine learning models for the wireless domain. You will conceptualize new solutions to operationalize and scale ML models for wireless networks/cellular chipsets and standards; propose implementation details; evaluate and simulate performance benefits; and analyze/diagnose system-level issues while collaborating across functional teams to meet or exceed system-level requirements and standards.

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Systems Engineering or related work experience.
• OR
• Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Systems Engineering or related work experience.
• OR
• PhD in Engineering, Information Systems, Computer Science, or related field.

Minimum Qualifications (Detailed)

• Master's degree in Engineering, Computer Science, Information Systems, Data Science, or related field.
• 2+ years of experience in systems engineering, software development, data engineering, or ML engineering (including taking models from prototype to deployment).
• Strong hands-on expertise applying ML to wireless/communications problems (e.g., signal processing, channel/PHY/MAC modelling, link/system-level simulation, and performance evaluation) using frameworks such as PyTorch or TensorFlow; familiarity with LLM concepts is a plus.
• Proficiency in Python and at least one systems programming language (C/C++/Java), with ability to build reliable, testable, production-quality code.

Preferred Qualifications

• 2+ years industry experience (or strong academic projects) applying ML to wireless/communications (signal processing) and one or more domains such as PHY/MAC/RRM, channel modelling, link-/system-level simulation, and performance trade-off analysis.
• Strong fundamentals in probability, statistics, and linear algebra underpinning modern ML/DL for communications.
• Strong analytical skills across the ML lifecycle: experiment design, dataset curation, metrics definition, model development/optimization (feature engineering, hyperparameter tuning), and evaluation of wireless ML solutions (accuracy, latency/complexity, robustness, and implementation cost).
• Strong hands-on with data structures/algorithms and performance-oriented system design for large-scale data processing, training, and inference.
• Strong software engineering for ML systems: Python plus C/C++/Java, clean APIs, testing, and maintainable code.
• Forward-looking mindset and awareness of emerging ML techniques relevant to wireless (e.g., graph neural networks and reinforcement learning).
• Plus: experience using GenAI/agentic approaches to accelerate wireless engineering workflows (simulation/test automation, log/telemetry analysis, and spec/document retrieval; RAG and tool/function calling).
• Plus: experience with cloud platforms (AWS/Azure/GCP), containerization/orchestration (Docker/Kubernetes), and scalable model serving/inference.
• Passion for learning and intellectual curiosity.