Deep Learning Model Efficiency Research Engineer

Qualcomm AI Research is looking for world-class researchers and engineers in machine learning and deep learning. Come join a high-caliber team of engineers building advanced machine learning technology, on-device AI solutions, and user friendly model optimization tools such as Qualcomm Innovation Center's AI Model Efficiency Toolkit (https://github.com/quic/aimet) to enable state-of-the-art networks to run on devices with limited power, memory, and computation. We are looking for talented researchers and engineers with experience in machine learning to enable embedded deep learning. We solve challenging problems to improve speed, accuracy, and power-consumption of deep neural networks. Your responsibility will be to apply our model efficiency tools on wide variety of use cases, provide detailed analysis, optimize algorithms, develop best practices and contribute to continuous evolution of model efficiency tools.

Required Skills:

• Bachelor's degree in Engineering, Computer Science, or related field.
• Strong understanding of Machine Learning fundamentals, strong programming skills with ML frameworks
• Excellent analytical, development, and debugging skills.
• Excellent interpersonal, written and oral communications skills

Preferred Skills:

• MS or PhD in Computer Science/Engineering with 1+ years of professional experience or equivalent experience.
• 2+ years of proven experience in algorithm design and software development for machine learning; proficiency in designing, implementing and training DL/RL algorithms in high-level languages/frameworks (PyTorch and TensorFlow).
• Strong background in at least one of the following fields: Machine learning theory / optimization methods; Model compression / quantization / optimization for embedded devices; Neural Architecture Search / kernel optimization; Computer vision; Audio and speech / NLP
• Experience with improving efficiency of AI algorithms for deployment, including familiarity with open source solutions such as Qualcomm Innovation Center's AI Model Efficiency Toolkit (https://github.com/quic/aimet)

Minimum Qualifications:

• 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.

Qualcomm is an equal opportunity employer and provides reasonable accommodations to individuals with disabilities during the application and hiring process.

Qualcomm expects its employees to abide by all applicable policies and procedures, including security requirements and protection of confidential information.

This role is part of the Engineering Group, specifically in Machine Learning Engineering.