As a Machine Learning Engineer at Qualcomm, you will focus on creating and implementing machine learning techniques and frameworks to enhance mobile, edge, auto, and IoT products. You will collaborate with cross-functional teams to drive digital transformation and develop state-of-the-art machine learning solutions. The role emphasizes real-time video analytics and advanced computer vision algorithms, requiring a strong background in applied statistics and performance-critical programming. You will also provide technical leadership and mentor engineers within the organization.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 4+ years of relevant work experience, or a Master's degree with 3+ years, or a PhD with 2+ years.
• 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 is preferred.
• 5+ years of experience with performance-critical programming in C++ and Python.
• 5+ years of experience with modern ML frameworks such as PyTorch, ONNX Runtime, TensorRT, TVM, OpenVINO, or Qualcomm’s AI toolchain.
• 3+ years of experience developing real-time edge AI systems with an emphasis on vision and multimodal perception.
• Strong background in applied statistics and evaluation of ML systems under real-world constraints.
• Familiarity with FFmpeg and GStreamer, along with knowledge of video codec and streaming technologies.

• Lead the design, development, and optimization of edge AI systems for real-time video analytics.
• Develop and integrate advanced computer vision and video analytics algorithms for AI cameras and edge solutions.
• Design and optimize real-time video processing pipelines using FFmpeg and GStreamer.
• Apply and evaluate machine learning techniques considering system-level constraints like bandwidth and latency.
• Prototype, validate, and productionize novel ML solutions aligned with product roadmaps.
• Lead experimental design, model training, benchmarking, and validation to ensure model accuracy and performance.
• Provide technical leadership, mentor engineers, and drive architectural decisions.
• Communicate technical strategy and results effectively to cross-functional stakeholders and senior leadership.

• Qualcomm offers competitive compensation, annual bonuses, stock programs, comprehensive healthcare coverage, retirement plans, wellness programs, parental leave, flexible work options, and professional development opportunities.