Whisper.ai is building the world’s first noise cancelling hearing aid system: it analyzes your audio in real time, automatically filtering out noise and amplifying the sounds you want to hear. Unlike traditional hearing aids, which simply amplify everything in the room, Whisper amplifies the person you’re listening to based on millions of audio prints it learns over time so it’s able to pick out who you’re listening to, even in the noisiest restaurant.
Based in San Francisco, Whisper is lucky to have the support of great investors including Sequoia Capital, First Round Capital, LUX Ventures, and more.
Building state-of-the-art deep learning acoustic models that improve people’s ability to hear is the centerpiece of the Whisper product, and great infrastructure and tools are what enables us to iterate quickly and develop new technology in this space. This machine learning infrastructure role spans everything from creating new data pipelines that ingest an ever-growing, proprietary real-world acoustic dataset, to building model quantization pipelines that will take new Tensorflow models and have them run efficiently on our embedded platform. This role is perfect for someone who wants to learn about AI and has a penchant for building new, low-maintenance solutions that make a company move faster.
- Software engineer with 3+ years in the industry.
- Proficient in Python and experience working with other systems languages (e.g. C/C++).
- Experience with common infrastructure and developer tools like Git, Linux, AWS/Google Cloud/Microsoft Azure.
- Familiarity with Linux operating system configuration and Docker.
- Able to build, maintain, and improve on production distributed systems for machine learning (e.g. Dask, PySpark, etc.).
- Comfortable with database set up, maintenance, and best practices.
- Excited to work within a broader team of engineers and researchers.
- Prefers simple, low maintenance solutions that get the core problem solved quickly.
- Experience working with modern, cloud-based infrastructure technologies like Kubernetes/GKE, Docker, Google Cloud/AWS/Azure, PySpark, Cloud Functions/AWS Lambda, etc.
- Familiarity with machine learning, including tools like Tensorflow and Tensorboard and hardware like TPUs.
- Experience working on an embedded or hardware environment or tuning for GPUs.
If you're interested in difficult and novel problems in embedded audio, immediate ownership of company defining decisions, top compensation, and work which directly helps 360MM+ people hear again - we'd love to hear from you.
Whisper.ai is an equal opportunity employer committed to a diverse workforce with an inclusive working environment for everyone to do their best work. We do not discriminate on the basis of race, ethnicity, religion, gender, gender identity, sexual orientation, age, marital status, veteran status, or disability status.