Senior Staff Engineer - Model Accuracy and AI Performance

About Qualcomm and the Role

Qualcomm is expanding its footprint in Riyadh to support growing infrastructure demands driven by Saudi Arabia's Vision 2030 digital transformation. The company is investing in advanced computing and data center capabilities aimed at AI, cloud, and connectivity. This role offers an exciting opportunity to contribute to cutting-edge data center operations and AI platform development in a fast-evolving technology hub.

Position Overview

The Qualcomm AI team designs hardware and software solutions across various markets including data center, edge, and automotive. We are looking for a Senior Staff Machine Learning Engineer to lead technical efforts in designing, optimizing, and deploying machine learning frameworks targeted at Qualcomm AI platforms. This role operates independently with a wide scope to influence technical direction and mentor others while remaining actively involved in hands-on engineering tasks.

Key Responsibilities

• Research, design, enhance, and implement components of machine learning frameworks and optimize graph performance and accuracy specifically for Qualcomm Neural Processing Units (NPUs).
• Evaluate software requirements, assess design feasibility within constraints, collaborate with architecture and hardware engineers, and implement appropriate software solutions for Qualcomm System on Chips (SoCs).
• Identify and troubleshoot system-level integration challenges alongside software development, integration, and testing teams.
• Develop and adapt the latest Generative AI methodologies for NPUs and architect innovative techniques aligned with Qualcomm SoC architectures.
• Provide technical leadership and mentorship by leading design reviews, guiding architecture discussions, and fostering best practices without direct management responsibilities.

Required Qualifications

• Bachelor's degree in Engineering, Information Systems, Computer Science, or a related discipline.
• Over 12 years of experience in Systems Engineering or a related technical field.
• In-depth knowledge of machine learning frameworks like PyTorch and TensorFlow.
• Proficient in model-level optimization techniques such as torch.compile.
• Expertise in diverse model architectures supported by literature and intuitive understanding.
• Strong understanding of a wide range of model architectures, machine learning algorithms, and techniques across different data modalities.
• Experience with training and inference workflows for machine learning models.
• Hands-on programming experience in C/C++ and Python, with at least 5 years of practice.
• Familiarity with object-oriented design and general software development best practices.
• Experience using source code and configuration management tools, particularly git.

Preferred Skills and Qualities

• Ability and willingness to work closely in a collaborative software development environment focusing on low-level implementation, including coding and testing, and interfacing with hardware and simulators.
• Experience in neural network architectures and ML compiler workload synthesis.
• Prior exposure to hardware accelerators and hardware-software co-design.
• Skills in profiling software performance and applying optimization techniques.
• A passion for pioneering advanced deep learning frameworks and algorithms optimized for mobile and embedded platforms.
• A research-oriented mindset combined with strong software development expertise.

Compensation and Benefits

• Competitive salary package including housing and transport allowance.
• Stock options (Restricted Stock Units) and performance-based bonuses.
• 16 weeks of fully paid maternity leave and 6 weeks of fully paid paternity leave.
• Employee stock purchase programs.
• Child education allowance.
• Relocation and immigration assistance if necessary.
• Life and medical insurance coverage.
• Live+ Well reimbursement for health and recreational memberships.

Additional Information

Qualcomm emphasizes equal opportunity employment, accommodating individuals with disabilities throughout the application process, and maintaining confidentiality of proprietary information. Applicants with equivalent experience to the stated qualifications will be considered if they demonstrate relevant competencies. The application process does not accept unsolicited submissions from recruitment agencies.