M/L Compiler Engineer

M/L Compiler Engineer
General Summary:
As a leading technology innovator we push 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 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. Our Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.
Minimum Qualifications:
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ 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 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.
Additional Job Description
Preferred Qualifications:
•    Master’s degree in Computer Science, Engineering, Information Systems, or related field.
•    5+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
•    5+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
•    5+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++)
•    5+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
•    3+ years experience working in a large matrixed organization.
•    2+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
•    1+ year in a technical leadership role with or without direct reports (only applies to positions with direct reports).
•    1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).
Principal Duties and Responsibilities:
•    Leverages advanced Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
•    Models, architects, and develops advanced machine learning hardware (co-designed with machine learning software) for inference or training solutions.
•    Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with hardware teams for joint design and development. 
•    Develops and applies machine learning techniques into products and/or AI solutions to enable customers to do the same.
•    Develops, adapts, or prototypes novel machine learning solutions aligned with and motivated by proposals or roadmaps for complex products and working features.
•    Oversees and conducts experiments to train and evaluate machine learning models and/or software.
M/L Compiler Engineer
General Summary:
As a leading technology innovator we push 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 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. Our Engineers collaborate with cross-functional teams to enhance the world of mobile, edge, auto, and IOT products through machine learning hardware and software.
Minimum Qualifications:
• Bachelor’s degree in Computer Science, Engineering, Information Systems, or related field and 2+ 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 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience.
OR
PhD in Computer Science, Engineering, Information Systems, or related field.
Additional Job Description
Preferred Qualifications:
•    Master’s degree in Computer Science, Engineering, Information Systems, or related field.
•    5+ years of experience with Machine Learning frameworks (e.g., Tensor Flow, Caffe, Caffe 2, Pytorch, Keras).
•    5+ years of experience in embedded system development and optimization with application to a specific problem domain in ML (e.g., NLP, multi-media).
•    5+ years of experience with one or more programming language suitable for machine learning (e.g., Python, R, C, C++)
•    5+ years of experience using statistics and probability (e.g., conditional probability, Bayes rule).
•    3+ years experience working in a large matrixed organization.
•    2+ years of experience with low level interactions between operating systems (e.g., Linux, Android, QNX) and Hardware.
•    1+ year in a technical leadership role with or without direct reports (only applies to positions with direct reports).
•    1+ year of work experience in a role requiring interaction with senior leadership (e.g., Director and above).
Principal Duties and Responsibilities:
•    Leverages advanced Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations.
•    Models, architects, and develops advanced machine learning hardware (co-designed with machine learning software) for inference or training solutions.
•    Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with hardware teams for joint design and development. 
•    Develops and applies machine learning techniques into products and/or AI solutions to enable customers to do the same.
•    Develops, adapts, or prototypes novel machine learning solutions aligned with and motivated by proposals or roadmaps for complex products and working features.
•    Oversees and conducts experiments to train and evaluate machine learning models and/or software.