Director Engineering - AI software stack

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 3+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. • 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. ​ Execution & Delivery • Oversee end‑to‑end 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). Team & Organizational Leadership • Build, mentor, and scale multi‑disciplinary AI/ML engineering teams (ML engineers, systems engineers, platform engineers). • Set technical direction, define career growth paths, and uphold a high bar for engineering excellence. • Foster a culture of ownership, accountability, and innovation. Minimum Qualifications • Bachelor’s degree in Engineering, Computer Science, or a related field. • 25+ years of industry experience in software engineering. • 20+ years of people management experience, including managing managers or senior technical leads and customers. • 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 Applicants: Qualcomm is an equal opportunity employer. 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