Principal Engineer - Chipset

Company

Qualcomm India Private Limited

Job Area

Engineering Group, Engineering Group > Software Engineering

General Summary

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.

Key Responsibilities

AI/ML Strategy & Platform Leadership

• Define and own the AI/ML technology roadmap aligned with business goals across automotive and edge AI platforms.
• Drive adoption of LLMs, VLMs/LVMs, multimodal AI, and agentic AI systems for real‑world, safety‑critical deployments.
• Influence platform and silicon‑level decisions by translating AI workload requirements into hardware and software capabilities.

Minimum Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 8+ years of Software Engineering or related work experience.

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 7+ years of Software Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field and 6+ years of Software Engineering or related work experience.

• 4+ years of work experience with Programming Language such as C, C++, Java, Python, etc.

Execution & Delivery

• Oversee delivery of AI systems from research to production, including model onboarding, optimization, validation, and lifecycle management.
• Ensure performance, power, latency, memory, and accuracy targets are met across heterogeneous compute (CPU/GPU/DSP/NPU).
• Establish best practices for model optimization (quantization, compression, batching, KV‑cache tuning, mixed precision).

Minimum Qualifications

• Bachelor’s degree in Engineering, Computer Science, or a related field.
• 18+ years of industry experience in software engineering.
• Strong background in AI/ML system design, not just model development.
• Hands‑on experience with ML frameworks (PyTorch, TensorFlow, ONNX) and edge/embedded deployment.
• Proven ability to deliver large‑scale, production AI systems in complex environments

Preferred Qualifications

Master’s or PhD in AI/ML, Computer Science, or related field.

Deep understanding of LLMs, VLMs/LVMs, multimodal and agentic AI architectures.

Experience with automotive or industrial platforms, embedded Linux/QNX, and real‑time constraints.

Familiarity with QNN‑like runtimes, inference SDKs, and heterogeneous acceleration.

Strong customer‑facing experience, including executive‑level technical discussions.

Track record of influencing product and platform roadmaps through technical leadership.

Experience in software architecture and design patterns

Knowledge of architectural approaches for large-scale software applications

Previous customer-facing experience is advantageous

Exposure to fine-tuning GenAI models and reinforcement learning considered a plus

Expertise in inference accuracy, throughput optimization, and edge deployment highly desirable

Lead system-level problem triage to identify root causes and communicate testing/debugging results to relevant stakeholders

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