Oculus
QualificationsPyTorchDeep learningTensorFlowC++Signal processingDoctoral degreeDoctor of Philosophy
Research Scientist: Computer Vision for Audio Responsibilities:
Independently implement state-of-the-art models and techniques on PyTorch, TensorFlow or other platforms.
Independently identify, motivate, and execute on medium to large hypotheses (each with many tasks) for model improvements through data analysis, and domain knowledge, and are able to communicate your learnings effectively.
Design, perform, and analyze online and offline experiments with specific and well thought-out hypotheses in mind.
Generate reliable, correct training data with great attention to detail.
Identify and debug issues in training machine learning models such as overfitting/underfitting, leakage, offline/online inconsistency consistently.
Understand the model architecture used, and the pros and cons of this for different hypotheses tested. In general, you have a good understanding of computer vision from an applied perspective, even though you may not be up-to-date with the state-of-the-art.
Minimum Qualifications:
PhD in the field of Deep learning, Machine Learning, Computer Vision, Computer Science, Computer Engineering or Statistics or a related field.
Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
4+ years experience with development and implementation of computer vision or deep learning algorithms.
3+ years experience with scientific programming languages such as Python, C++, or similar.
Demonstrated experience in implementing and evaluating work and end-to-end prototypical learning systems.
Preferred Qualifications:
Experience with AV learning or egocentric learning, scene understanding, audio signal processing or similar.
Experience working with acoustic or speech datasets.
Proven track record of achieving significant results and innovation as demonstrated by first-authored publications and patents.
Interpersonal skills: cross-group and cross-culture collaboration.
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