Staff Software Engineer

Qualcomm • Santa Clara, CA

1d

About The Position

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 discovery and utilization of state-of-the-art machine learning solutions over a broad set of technology verticals or designs. Qualcomm Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.

Requirements

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ 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 3+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
• OR PhD in Computer Science, Engineering, Information Systems, or related field and 2+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.

Nice To Haves

• Master’s degree or PhD in Computer Science, Electrical/Computer Engineering, Robotics, or a related field with specialization in edge AI, computer vision, or embedded ML.
• 5+ years of experience with performance‑critical programming in C++, Python, including hardware‑aware optimization.
• 5+ years of experience with modern ML framework such as PyTorch, ONNX Runtime, TensorRT, TVM, OpenVINO, or Qualcomm’s AI toolchain including SNPE, QNN.
• 3+ years of experience developing real‑time edge AI systems with emphasis on vision, multimodal perception, and sensor fusion.
• Strong background in applied statistics, probabilistic modeling, and evaluation of ML systems under real‑world constraints such as latency, thermal limits, and bandwidth.
• Familiar with FFmpeg, GStreamer with solid knowledge of video codec and streaming technologies.
• Experience with computer vision and intelligent video analytics, including object detection, tracking, re‑identification, camera geometry and calibration, and cross‑camera association.
• Experience working in large cross‑functional organizations involving hardware, firmware, cloud, and product teams.
• Experience leading technical initiatives, mentoring engineers, or driving architectural decisions.
• Experience presenting technical strategy or results to senior leadership.

Responsibilities

• Lead the design, development, and optimization of edge AI systems for real-time video analytics, spanning model architectures, inference pipelines, and runtime frameworks deployed on AI camera and embedded platforms.
• Develop and integrate advanced computer vision and video analytics algorithms to deliver robust, production-grade AI cameras and edge computer vision solutions.
• Design and optimize real-time video processing pipelines, leveraging FFmpeg, GStreamer, and streaming protocols to handle high-throughput, low-latency video ingestion, preprocessing, inference, and post-processing.
• Apply and evaluate machine learning techniques under real-world constraints, incorporating system-level considerations such as bandwidth, compute budget, memory footprint, thermal limits, and end-to-end latency.
• Prototype, validate, and productionize novel ML solutions aligned with product roadmaps, transforming research concepts into reliable customer-facing features.
• Lead experimental design, model training, benchmarking, and validation, establishing metrics, evaluation frameworks, and best practices to ensure model accuracy, robustness, and system performance at scale.
• Provide technical leadership across the organization, mentoring engineers, reviewing designs, and driving architectural decisions that shape the long-term evolution of the ML and edge AI platform.
• Communicate technical strategy, trade-offs, and results effectively to cross-functional stakeholders and senior leadership, influencing product direction and execution.

Benefits

• Competitive annual discretionary bonus program
• Opportunity for annual RSU grants
• Highly competitive benefits package designed to support your success at work, at home, and at play.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Number of Employees: 5,001-10,000 employees