Q

Qualcomm

Designs mobile chips and licenses wireless patents

Director Engineering - AI Software Stack, Software Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • A bachelor's degree in Engineering, Information Systems, Computer Science, or a related field and at least 3 years of software engineering or related work experience; or a master's degree in those fields and at least 2 years of related experience; or a PhD in those fields and at least 1 year of related experience.
  • At least 2 years of academic or work experience with a programming language such as C, C++, Java, or Python.
  • A bachelor's degree in Engineering, Computer Science, or a related field.
  • At least 25 years of industry experience in software engineering.
  • At least 20 years of people management experience, including managing managers or senior technical leads and customers.
  • Strong background in AI/ML system design, beyond model development.
  • Hands-on experience with ML frameworks such as PyTorch, TensorFlow, and ONNX, and edge or embedded deployment.
  • Proven ability to deliver large-scale, production AI systems in complex environments.

Responsibilities

  • 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.
  • 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 including CPU, GPU, DSP, and NPU.
  • Establish best practices for model optimization, including quantization, compression, batching, KV-cache tuning, and mixed precision.
  • Build, mentor, and scale multidisciplinary AI/ML engineering teams, including ML engineers, systems engineers, and platform engineers.
  • Set technical direction, define career growth paths, and uphold engineering standards.
  • Foster a culture of ownership, accountability, and innovation.
  • Lead system-level problem triage to identify root causes and communicate testing and debugging results to relevant stakeholders.

Desired Qualifications

  • A master's or PhD in AI/ML, Computer Science, or a related field.
  • Deep understanding of LLMs, VLMs/LVMs, multimodal AI, 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.
  • A 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.
  • Exposure to fine-tuning generative AI models and reinforcement learning.
  • Expertise in inference accuracy, throughput optimization, and edge deployment.

About the Company

Qualcomm

Designs mobile chips and licenses wireless patents

Qualcomm designs the Snapdragon processors and modems inside many Android phones, and it licenses its wireless patents to device makers around the world. It helped commercialize CDMA, the cellular technology behind 3G networks, and its patents cover core parts of the 4G and 5G standards that phones use to connect. The company does not run its own chip factories; contract foundries make its chips, which it sells to makers of phones, PCs, cars, and connected devices. Device makers also pay Qualcomm royalties for using its patented technology, which forms a second business alongside chip sales. Qualcomm was founded in 1985 and is based in San Diego, California.

Company size
10,001+
Company stage
IPO
Headquarters
San Diego, CA
Founded
1985

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