AI ML Engineer Senior

Qualcomm is a leading technology company specializing in wireless telecommunications and AI innovation.
Machine Learning
Senior Software Engineer
In-Person
4+ years of experience
AI

Description For AI ML Engineer Senior

We are looking for Software Engineers to help develop our AI software stack. The team is comprised of experts that span the full stack from software architecture, algorithm development, kernel optimization, down to hardware accelerator block architecture and design.

Responsibilities:

  • Development of AI SW stack framework enhancements for optimal resource usage while running a neural network on Qualcomm hardware
  • Development of software tools for profiling, and debugging to support rapid deployment of new neural networks in this fast-changing field
  • Evaluating and optimizing neural networks runtime performance and accuracy
  • Working with customer teams to enable state of the art network models and new AI SW features to meet customer use-cases
  • Collaborating with AI Hardware and architecture teams to continuously improve our AI solution
  • Being an active contributor to the development process to ensure commercial quality software releases

Minimum Qualifications:

  • Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field.
  • 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

Additional Preferred Qualifications:

  • 5+ years' software development experience
  • Excellent programming capability and analytical, development, and debugging skills
  • Curiosity and willingness to continually learn new things and propose new ideas
  • Experience in C/C++
  • Android, embedded Linux software development
  • Exposure to RTOS, kernel drivers, Computer Architecture
  • Some experience with Python and Git
  • Experience with Python numpy and deep learning frameworks such as Caffe, TensorFlow, PyTorch
  • Excellent communication skills (verbal, presentation, written)
  • Ability to collaborate across a globally diverse team and multiple interests

Qualcomm is an equal opportunity employer and is committed to providing reasonable accommodations to support individuals with disabilities in the application and hiring process.

Join Qualcomm to work on cutting-edge AI technologies, collaborate with experts, and contribute to world-changing innovations. Unlock your full potential in a supportive, inclusive culture with opportunities for continuous learning and growth.

Last updated 11 hours ago

Responsibilities For AI ML Engineer Senior

  • Develop AI SW stack framework enhancements for optimal resource usage
  • Create software tools for profiling and debugging neural networks
  • Evaluate and optimize neural networks runtime performance and accuracy
  • Work with customer teams to enable state-of-the-art network models and AI SW features
  • Collaborate with AI Hardware and architecture teams to improve AI solutions
  • Contribute to the development process for commercial quality software releases

Requirements For AI ML Engineer Senior

Python
Java
Linux
  • Bachelor's or higher degree in Engineering, Information Systems, Computer Science, or related field
  • 2+ years of Software Engineering or related work experience
  • 2+ years of academic or work experience with Programming Languages such as C, C++, Java, Python, etc.
  • Experience in AI software stack development
  • Knowledge of neural networks and AI frameworks
  • Proficiency in software development tools and practices

Benefits For AI ML Engineer Senior

  • World-class health coverage for employees and eligible dependents
  • Financial programs to help build a secure future
  • Self and family resources for emotional/mental strength and resilience
  • Wellbeing programs to support work-life balance
  • Continuous learning and development programs
  • Tuition reimbursement
  • Mentorship opportunities

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