Machine Learning Infrastructure Engineer

Location : Redmond, WA. Write clean, maintainable code, debug complex problems that span systems, prioritize ruthlessly, and get things done with a high level of efficiency. Create robust, flexible, and scalable ML tooling and infrastructure which supports research scientists to leverage Client's powerful infrastructure (through e.g., source control, distributed compute clusters, data storage). Coordinate with a large set of internal infrastructure and tool teams across the lab and across Client to evaluate and integrate with existing systems. Work collaboratively as part of a multifunctional team where communication, documentation and teamwork are highly valued Learn constantly, dive into new areas with unfamiliar technologies, and embrace the ambiguity of AR/VR problem solving Job Responsibilities: BS degree in Computer Science or related field, or equivalent work experience. 4+ years industry experience with deep learning frameworks in Python, such as PyTorch or TensorFlow. 2+ years industry experiences working with large, complex data sets for machine learning, including capture and annotation. Demonstrated experience implementing and evaluating working and end-to-end prototypical learning systems. Experience working with high performance or distributed compute solutions. Some deployment and continuous integration experience. Skills: We're looking for Python and infrastructure focused software engineers. PyTorch or similar AI/ML engines. Distributed infrastructure. Working with complex, real-world multimodal data. Audio. AR/VR. Education/Experience: Familiarity with Machine Learning for Audio, multimodal or DSP purposes Experience working in the AR/VR application space. Experience in Linux or Windows shell scripting. Ability to gather requirements and work closely with researchers to develop novel solutions History of writing code to support the execution of research initiatives