Nuvia
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 Machine Learning Engineer, you will create and implement machine learning techniques, frameworks, and tools that enable the efficient utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs.
This job description outlines an exciting role focused on developing Generative AI systems and building proof of concepts. The position involves end-to-end scenario pipeline demonstration and design advancements, utilizing both new Generative AI and traditional AI/ML techniques around foundation models.
The role is cross-functional, requiring collaboration with multiple teams including system software, hardware, customer engineering, and product teams, all working on various Snapdragon-powered devices. This is a unique opportunity to work with cutting-edge hardware and contribute to the future of high performance across the Snapdragon chipset portfolio.
Minimum Qualifications:
• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 4+ years of Software Engineering or related work experience.General Summary
In this position you will be responsible for assisting with the software design and development of the Qualcomm AI Stack, SDKs and associated tools, targeting Snapdragon platforms. You will have the opportunity to show your passion for software design and development with your analytical, design, programming, and debugging skills. The highly creative teams consist of Core AI Platform and System experts who work on the latest Snapdragon hardware and software Generative AI/ML innovations across mobile, automotive, PC, and XR.
Responsibilities
Applied research and SW development in AI-ML - Introduce /Optimize new SOTA parallel decoding schemes.
Software development of the AI - Latest LLM/LVM backone architecture on-boarding and optimizations (e.g, MoE, MMDiT).
Applied research and development for AI video pipeline optimizations on NPU.
Minimum Qualifications
7-12 years of experience in AI-ML domain with strong working knowledge of model building, model optimization, quantization, NAS.
Strong communication skills (verbal, presentation, written)
Preferred Qualifications
AI/ML System Optimization: Over 5 years of experience in system optimization and inference pipeline.
Edge GenAI Deployment: Hands-on experience with workflows and infrastructure for LLM, LMM, LVM, and LoRA.
Platform Focus: Primary experience with Android and Linux using C/C++.
Inference Frameworks: Practical experience with edge machine learning inference frameworks (SNPE, QNN, LiteRT, ExecuTorch, MLIR, etc.).
Experience in Neural Network optimization: NAS, Advance architectural search strategies, Hyperparameter optimization, Model compression and pruning, Meta learning and transter
Machine Learning Optimization Knowledge: Foundational understanding of machine learning models, especially post-training optimizations (compression, quantization, Graph optimization, knowledge distillation, SOTA Graph methodologies for Heterogeneous computing etc.).
Tech Leadership: Capability to contribute to commercial software design.
Generative AI Models: Familiarity with Generative AI model architectures.
Machine Learning Accelerators: Experience in utilizing and optimizing algorithms for Snapdragon-powered devices or similar edge AI accelerators.
Gen AI/ML Trends: Up to date with the latest trends and optimizations in Generative AI/ML, Agentic AI, etc.
Self-Motivation: Ability to work independently without supervision.
Strong Communication: Emphasis on strong communication skills.
Education Requirements
Required: Phd/Mtech from reputed institution, Information Systems, Computer Science, or related field.
Preferred: Phd/Mtech in Computer Science, Computer Engineering, or Electrical Engineering
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