Meta AR/VR Job | ML Audio Research Engineer
Job（岗位）: ML Audio Research Engineer
Type（岗位类型）: Hardware
Citys（岗位城市）: Sunnyvale, CA | Redmond, WA | Remote, US
Date（发布日期）: Before 2021-12-14
Summary（岗位介绍）
The Facebook Reality Labs Audio Tech team brings together world-class experts to develop and ship groundbreaking products at the intersection of hardware, software, and content. We have a clear mandate to ship products at scale. In particular, seemingly impossible products that define new categories that advance Facebook’s mission of connecting the world. The team is focused on algorithm development and commercialization of real world products.
Qualifications（岗位要求）
BS in Electrical Engineering, Computer Science, Computer Engineering, Applied Mathematics, or equivalent relevant experience
Understanding of ML, DSP and DNNs theory
3+ years of experience with one or more deep learning/ML frameworks such as Tensorflow, PyTorch or Keras
3+ years of programming experience working with C/C++
Experience with a full product lifecycle from concept to deployment
Description（岗位职责）
Research and develop audio ML based audio enhancement algorithms for communications, and music enhancement with Deep learning and DSP methods in C/C++ and deep learning frameworks
Prototype hybrid ML solutions with deep learning and signal processing techniques
Validate and improve deep learning models to enable implementation of these ML/DNN models in low power real time embedded hardware
Define, develop and debug real-time audio system software for forward looking products and user experiences
Interface with Facebook AI Research, audio algorithm scientists, ML/AI engineers and other product teams on productizing research algorithms
Additional Requirements（额外要求）
PhD in Electrical Engineering, Computer Science, Computer Engineering, Applied Mathematics
Experience developing audio signal processing algorithms such as noise suppression, acoustic echo cancellation, sound field classifications or machine learning algorithms
Experience with real-time machine learning systems, training data augmentation and large dataset preparations
Experience working with GPU, cloud systems, profiling/low-level optimizations, Cuda/CuDNN
