AI Software Engineer, Staff

A global leader in wireless technology innovation and pioneering company in on-device AI and 5G technology development.
Taipei, TaiwanHsinchu, Hsinchu City, Taiwan
Machine Learning
Staff Software Engineer
In-Person
5,000+ Employees
10+ years of experience
AI · Enterprise SaaS

Description For AI Software Engineer, Staff

Qualcomm is seeking a Staff AI Software Engineer to join their innovative team in Taiwan. This role sits at the intersection of AI and mobile technology, focusing on developing cutting-edge solutions for Qualcomm's AI Stack. The position involves working with global AI R&D teams to advance AI applications across Mobile, Automotive, IoT, and HPC devices. The ideal candidate will have 10+ years of software engineering experience, strong expertise in AI/ML development, and proficiency in multiple programming languages. They will be responsible for developing and optimizing AI-related computations, working with neural network frameworks, and ensuring high performance of AI systems. The role offers opportunities to work with industry-leading technology, contribute to groundbreaking AI innovations, and shape the future of mobile computing. Qualcomm provides comprehensive benefits including health coverage, financial planning support, and professional development opportunities. This position represents a unique opportunity to work at the forefront of AI technology while contributing to products that impact billions of users worldwide.

Last updated 8 hours ago

Responsibilities For AI Software Engineer, Staff

  • Contribute to system software and tool development for ML computing SDKs
  • Collaborate with neural network frameworks like PyTorch and TensorFlow
  • Extend neural net engine to support latest DNNs
  • Optimize for next-gen hardware acceleration cores
  • Validate engine performance and accuracy
  • Partner with industry leaders in machine learning technology
  • Develop and maintain AI applications for Mobile, Automotive, IoT, and HPC devices

Requirements For AI Software Engineer, Staff

Python
Java
  • Bachelor's degree in Computer Science, Electrical Engineering, or related field
  • Proficiency in programming languages such as C, C++, Java, Python
  • Experience in large-scale software projects, particularly in AI-related software development
  • Proficiency with version control systems like Git and tools like Gerrit and JIRA
  • Familiarity with Windows and Android development environments
  • Strong understanding of system architecture and software design principles
  • 10+ years of Software Engineering experience
  • Experience in AI-related computations
  • Knowledge of Deep Learning/CNN fundamentals

Benefits For AI Software Engineer, Staff

Medical Insurance
401k
Education Budget
  • World-class health coverage for employees and dependents
  • Financial planning and future preparation programs
  • Emotional/mental health support
  • Wellbeing programs
  • Tuition reimbursement
  • Mentorship programs

Interested in this job?

Jobs Related To Qualcomm AI Software Engineer, Staff

Sr Staff Engineer - System solution AI Center of Excellence

Lead AI systems solution development at Qualcomm's Center of Excellence, focusing on inference accelerators and edge AI applications across automotive, cloud, and IoT domains.

System SW Architecture - ML Acceleration Lead Engineer

Lead ML Acceleration Engineer role at Qualcomm focusing on optimizing ML/AI performance through advanced CPU and NPU features, requiring expertise in ARM architecture and ML frameworks.

Staff AI Software Engineer

Staff AI Software Engineer position at Qualcomm Atheros, focusing on AI/ML model development and optimization for edge devices, offering competitive compensation and comprehensive benefits.

Sr. Staff Software Engineer

Senior Staff Software Engineer position at Qualcomm focusing on AI Stack development and machine learning implementation for Snapdragon platforms.

Staff GenAI Evaluation Engineer - Qualcomm Research

Staff GenAI Evaluation Engineer position at Qualcomm Research focusing on machine learning algorithm evaluation and optimization for embedded GenAI systems.