Director Engineering - Ai Software Stack

Qualcomm · Bengaluru

  • Experience25–30 yrs
  • SalaryNot disclosed
  • Work modeonsite
  • Posted23 Sept 2026

About Qualcomm

Qualcomm is hiring in Bengaluru in semiconductors electronics. This role looks for around 25+ years of experience.

Skills

  • AI/ML system design
  • C
  • C++
  • Java
  • Python
  • PyTorch
  • TensorFlow
  • ONNX
  • model optimization
  • edge/embedded deployment
  • software architecture
  • software design patterns

The role

An engineering manager at a semiconductor technology company defines AI / ML Engineer roadmaps and delivers Generative AI Engineer systems for automotive and edge platforms, applying PyTorch and TensorFlow to production model optimization and deployment. The role also guides multidisciplinary engineering teams and influences hardware-software architecture.

Full job description

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 realworld, safetycritical deployments.

Influence platform and siliconlevel 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. ORMaster''s degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. ORPhD 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 endtoend 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, KVcache tuning, mixed precision).

Team Organizational Leadership

Build, mentor, and scale multidisciplinary 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

Bachelors 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.

Handson experience with ML frameworks (PyTorch, TensorFlow, ONNX) and edge/embedded deployment.

Proven ability to deliver largescale, production AI systems in complex environments

Preferred Qualifications

Masters 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 realtime constraints.

Familiarity with QNNlike runtimes, inference SDKs, and heterogeneous acceleration.

Strong customerfacing experience, including executivelevel 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