Machine Learning Researcher – On-device AI theory and algorithm

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Job Description:

**Job Id**


Job Title

Machine Learning Researcher – On-device AI theory and algorithm



Qualcomm Technologies, Inc.

Corporate Research & Development at

Job Area

Engineering – Software


South Korea – Seoul


We are making AI technology be around us at edge devices, attend and assist people and learn from interaction without many labels, together with other devices in a federated way. We are based in Seoul and work together with our other team members in San Diego, Amsterdam, and Beijing.

We are looking for the deep-learning researchers interested in developing new theories and algorithms on the following areas:

• Unsupervised / semi-supervised / self-supervised learning

• Federated learning

• Meta-Learning: few-shot learning

• Life-long learning

• Domain adaptation / knowledge transfer

• Deep generative models

• Representation learning

• Adversarial attacks, examples

• Anomaly detection

• Multi-modal context aware

The developed theories and algorithms can be applied to computer vision, audio, and speech tasks such as image classification, image generation, video classification, audio scene detection/classification, automatic speech recognition, and speaker identification/verification.

Also, the research results can be published as a conference paper.

The technologies to develop can be deployed on the mobile device applications and has a great worldwide impact on the on-device learning algorithms using Qualcomm chips.

Minimum Qualifications

• Machine learning knowledge and experiences

• Recent deep learning research experiences

• Algorithm implementation experiences using python with deep learning platform, e.g. PyTorch, TensorFlow.

Education Requirements

MS or Ph.D.s degree in Electrical Engineering or Computer Science or related area

EEO Employer: Qualcomm is an equal opportunity employer; all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or any other protected classification.