Dsp And Ml Prototyping Engineer

We’re looking for a hands-on engineer, focused on DSP and ML prototyping, who has a passion for bringing amazing new experiences to life. Bose has a strong history of combining creative thinking with cutting-edge technology in the audio domain. We are seeking candidates who are passionate about audio systems to help us shape the next chapter in the future of Bose!

Description:

Our team develops and prototypes new audio experiences to shape the next generations of Bose products. Our algorithms must run in real-time, on wearable devices, for applications such as voice pickup, hearing augmentation, enhanced music experiences and beyond. The ideal candidate will help us bring these experiences to life. As part of the team, you will work with experts in deep learning, digital signal processing, software engineering and psychoacoustics to prototype and implement new algorithms. Our work spans from classical DSP and controls to cutting edge machine learning (ML) approaches.

Responsibilities:

- A substantial portion of your time will be devoted to prototyping and implementing real-time ML/DSP algorithms on portable/wearable platforms.

- You will integrate your novel solutions into new and existing systems and platforms to deliver new proofs of concept.

- You will characterize and demonstrate these solutions in the lab and share them across our research teams

Experience:

- Completed a degree in ML, DSP, Computer Science, Music Technology or a related field. Graduate-level degrees are preferred.

- Ideally 5 years of work experience porting complex audio algorithms to real-time systems.

- Demonstrable experience in building real-time audio processing systems

Skills:

- Strong audio software/firmware development skills across a wide range of chipsets.

- Strong ability to implement audio processing pipelines in C++

- Practical knowledge of applied digital signal processing (DSP).

- Competency with audio measurements

- Strong communication skills.

Nice to Have:

- Familiarity with ML algorithms in Python and TensorFlow/PyTorch

- Familiarity with Control systems for Active Noise Cancellation

- Familiarity with Sigma Studio, Simulink, Matlab

- Familiarity with developing on real-time Linux-based systems

- Familiarity with TFLite, ONNX, NeuralMagic, TensorRT etc

- Familiarity with standard version control practices.

- Familiarity with data acquisition methods