Qualcomm's Computer Vision Systems team is seeking a Machine Learning Engineer to develop advanced computer vision algorithms for various applications including mobile devices and autonomous vehicles. The ideal candidate will have a strong background in both computer vision and deep learning, along with hardware and software implementation experience. This role involves end-to-end ownership of machine learning models and their integration into Qualcomm Snapdragon platforms. The engineer will also serve as a technical lead, influencing system-level architecture and driving solutions from research to production deployment.

• Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 8+ years of relevant experience, or a Master's degree with 7+ years, or a PhD with 6+ years.
• 5+ years of experience with machine learning frameworks such as TensorFlow, Caffe/Caffe2, PyTorch, or Keras.
• 5+ years of experience with low-level interactions between operating systems and hardware.
• 5+ years of experience in embedded system development and optimization applied to machine learning.
• 5+ years of experience with programming languages suitable for machine learning, such as Python, R, C, or C++.
• Experience using statistics and probability in machine learning contexts.

• Research the latest trends in computer vision and develop models for real-world applications.
• Train and optimize machine learning methodologies and build training pipelines.
• Analyze bottlenecks in machine learning workloads on Qualcomm hardware and software stacks.
• Own technical direction across projects and influence system-level architecture.
• Serve as a technical lead for teams developing and prototyping machine learning solutions.
• Act as a technical expert in machine learning model architecture and collaborate with hardware engineers.

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