Job description
Established in 2017, Whisper is a team of artificial intelligence, hearing care, hardware, and software experts coming together to solve the challenge of providing better hearing. We set out to make the Whisper Hearing System so our parents, grandparents, friends and teammates can have a tomorrow that sounds even better than today.
Based in San Francisco, Whisper is lucky to have the support of great investors including Sequoia Capital, First Round Capital, Quiet Capital, IVP, and more.
THE ROLE
Signal processing and machine learning are at the core of Whisper’s innovative hearing aid. As an Audio Machine Learning Engineer, your work will directly shape the daily audio experience of every Whisper patient. You will help plan and execute against ambitious audio machine learning roadmaps and advance the state of the art in edge computing, acoustic simulation and training systems, perceptual loss functions, and acoustic machine learning performance for hearing aids.
RESPONSIBILITIES
This is a very applied role where you will improve patients' daily lives by defining data collection and labeling strategies, developing and improving offline product iteration tools, improving embedded inference capabilities, working cross functionally with hardware and firmware in making forward looking architecture decisions, and train models to improve denoising and signal processing in a state of the art hearing aid.
MINIMUM QUALIFICATIONS
3+ years experience shipping machine learning products on audio, image, time series, or related datasets.
Familiarity with classical signal processing techniques.
Strong experience developing training data, metrics, and tools to improve model performance based on field data and product input.
Experience with Tensorflow and Keras or other ML frameworks, distributed training, and cloud infrastructure.
Strong understanding of supervised and unsupervised machine learning techniques and deep learning models.
BS, MS, or PhD in CS, Statistics, or related technical field.
Proficient in Python and familiarity with other systems languages (e.g. C/C++).
Clear communication skills and a team multiplier.
BONUS POINTS
Passion for or prior experience in edge compute and audio processing.
Experience working with low latency systems.
Experience with GCS, TPUs, Pandas, and visualization tools.
Published papers in top machine learning conferences.
A personal connection to improving hearing health.
If you're interested in difficult and novel problems in embedded audio, immediate ownership of company defining decisions, competitive compensation, and meaningful work that could help 430MM+ people hear again - we'd love to hear from you.
Please mention that you found the job at Jobhunt.ai
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