AI/ML Platform Architect - Engineer, Principal

Qualcomm•San Diego, CA

About The Position

We are looking for an experienced Windows platform architect to drive AI system performance and power enhancements into the SW and HW stacks and SW tools of state-of-the-art machine learning solutions on Snapdragon platform such that the AI performance and power is delivered to final applications while keeping application developer experience and ease of deployment competitively high. As a senior member of the team responsible for competitive advantages in end-to-end delivery of AI functionality, performance, power on Snapdragon compute platform, you will have opportunity to drive joint HW-SW design and architecture spec while representing requirements of Windows on Snapdragon application developers for multiple AI use-cases and ensure the Snapdragon AI platform, and tools deliver the industry leading performance and power including necessary security requirements. You will also study Enterprise agentic AI workflows, define, and drive implementation of on-device AI platform components such that Snapdragon becomes the preferred choice for Enterprise AI PCs. You will work closely with software and hardware architects, project engineers, product managers, customer engineers, OEMs, OS partners and application developers. Ideal candidate has extensive experience in architecture aware AI Model system performance optimization on Windows PC/Laptop, architecture aware benchmarking, and performance breakdown analysis with GPU, NPU, and knowledge of state of the art in AI for multiple domains such as Computer Vision, Audio, Generative AI, Agentic AI.

Requirements

Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 7+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR PhD in Computer Science, Engineering, Information Systems, or related field and 6+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
Excellent understanding of AI frameworks (e.g., TensorFlow, PyTorch), GPU/NPU programming, and parallel computing.
Good Understanding of complete Software stack and familiarity with AI and other multimedia hardware acceleration technologies
Experience with performance optimization of AI application on Windows using processor specific optimization tools/libraries/primitives on GPU, NPU
Strong background in end to end system performance analysis using profiling tools, and algorithmic modification methods for performance improvement is essential
Knowledge of state of the art in Agentic AI
Knowledge of computer architecture, embedded system implementations
Strong software engineering principles are essential
Proficiency in programming languages such as Python, C++
Excellent communication skills to articulate complex technical concepts to non-technical and technical stakeholders.
Strong leadership abilities to motivate and guide development teams.
Detail-oriented with strong problem-solving, analytical, and debugging skills with the ability to think strategically and drive innovative solutions.
Demonstrated ability to learn, think and adapt in a fast-changing environment
Familiarity with software development methodologies, version control systems, and agile project management practices.
15+ years experience in High Performance Computing System Engineering or Software with 5+ years in AI system optimization
Masters or PhD in Computer Science or Electrical Engineering

Nice To Haves

Experience with large language models/foundational models development and deployment a plus

Responsibilities

Understand trends in ML network design, through customer engagements and latest state of the art, and determine how this will affect both SW and HW design
Analyze bottlenecks in end to end use-cases and application of ML/AI algorithms and workloads on exploratory and existing Qualcomm HW and SW stacks through simulation and on-device characterization
On-device correlation and tuning of algorithm versus pre-silicon predictions
Analyze Enterprise AI workflows for common user personas and propose components that make Snapdragon AI PCs work complimentarily with cloud AI components of the enterprise workflow to deliver measurably increased productivity and user-experience for enterprise users
Interface with other cross-site and cross-functional teams to arrive at best-in-class performant reference implementations, tools, and documentation that are directly leveraged by 3rd party app developers
Analyze, develop, propose new features and designs to system design of next gen SoCs that reduce performance bottlenecks through the workflow

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