One of the big challenges product manufacturers face is to meet the market demand for battery-operated, always-on, always-sensing products without sacrificing sensing capabilities, maintaining reasonable battery-life, and keeping data secure and local.
Aspinity's novel and patented analog machine learning (ML) solution marks a paradigm shift in the way sensor data is analyzed for a multitude of end-user applications. Just as the brain makes sense of its multi-modal sensory input by focusing higher-order cognition on salient characteristics, Aspinity enables developers to extract "sense" from sensors before the data is ever digitized, which reduces power consumption and allows the system to focus higher power compute resources on relevant information.
With already established applications for voice control, sound classification, machinery monitoring, and distributed power grid monitoring, Aspinity's programmable analog processing technology is positioned to be the key abstraction layer for the physical world at a time when new user interface paradigms (touch to voice to …) and new monitoring capabilities are transforming industries. Join us as we build this new analogML framework!
Role & Responsibilities
Aspinity is looking to hire an experienced machine learning architect to focus on developing and deploying algorithms that use sensor data to detect, classify, and understand the environment around our end user applications. As the Director of Machine Learning, you will be responsible to lead the research, development, simulation, implementation, integration, and testing of sensor data algorithms to help develop a model of the world in numerous applications. You will serve as a coach and mentor for your team for best practices in dataset definition, algorithm research, implementation, and presentation/visualization.
You will serve as a key leader in the organization and be part of a cross-functional team that is charged with developing product strategy and realization.
- Lead and grow the algorithm research and development team, defining novel event detection and classification strategies and realizing these strategies in Aspinity hardware
- Develop and implement ML and signal processing algorithms into production software optimized for analog signal processing
- Consult with customers as they implement their ideas on our design platform
- Define requirements for Aspinity’s developer platform and SDK
- Mentor team members in their research, implementation, and communication abilities
Required Experience:
- A Master’s degree in Computer Science, Computer Engineering or Electrical Engineering;
- 10-15 years’ experience with machine learning—including development of novel network architectures, optimization techniques, production classification models, and maintenance of ML pipelines. Experience with deployment to energy-constrained hardware is a plus;
- Understanding of probabilistic methods like Bayesian filtering and graphical inference, state estimation, and time synchronization of multiple-sensor data sets is necessary;
- Familiarity with scientific computing is required;
- Experience with machine learning tools such as PyTorch or TensorFlow is required;
- Excellent written and verbal communication skills;
- Interest in managing and developing people;
- Flexible and willing to accept a change in priorities as necessary.
Other Information:
