About the job
About Tacit
Tacit is a deep tech startup based in San Francisco, focused on advancing human-computer interaction through new hardware. The company is backed by investors including General Catalyst, Khosla Ventures, and Greylock Partners. The founding team brings experience from Stanford, BrainGate, Oculus, and Tesla. While much of the work is confidential, the team tackles ambitious engineering problems to deliver novel products.
Role Overview
The Computational Neuroscientist will help develop new approaches for data analysis, improve signal extraction, and strengthen Tacit's technology infrastructure. The role involves running and interpreting experiments on proprietary systems, drawing insights to guide future data collection, and refining decoding algorithms. Work includes direct interaction with signals from custom hardware and studying how performance scales across different user groups.
This is a full-time, on-site position in San Francisco (5 days per week).
What You Will Do
- Design, implement, and evaluate algorithms to extract features from biosignals for machine learning use.
- Iterate quickly on experiments to test new hardware prototypes and improve data collection methods.
- Develop analytical tools for visualizing and assessing data quality.
- Work closely with hardware and electrical engineers to improve the sensing stack.
Requirements
- PhD in neuroscience, biomedical engineering, machine learning, computer science, or a related field (or equivalent industry experience).
- Skilled in Python and PyTorch.
- Experience collaborating across diverse teams and adapting to new technical domains.
- Background in dimensionality reduction and time series data analysis.
- Self-driven, adaptable, and resourceful approach to work.
- Strong communication skills and a collaborative mindset.
- Comfort working in a startup setting and able to contribute independently.
Preferred Qualifications
- Experience with real-time human-machine interaction technologies, such as automatic speech recognition or closed-loop systems.

