One of our early-stage, deep tech startup investments based in San Francisco is developing innovative hardware that rethinks human-computer interaction. Founding team is from Stanford, BrainGate, Oculus, and Tesla.
Job Overview:
As a computational neuroscientist, you will develop new tools and techniques for understanding our data, extracting as much signal out as possible, and improving our technology stack. You’ll be responsible for running and analyzing experiments using our system, interpreting results to inform future data collection, and improving our decoding algorithms. This role will feature hands-on work with our basic signals coming off custom hardware all the way up to studying performance scaling across large numbers of people.
Responsibilities:
• Design, implement, and test algorithms for data feature extraction from bio-signals for use in machine learning models
. • Rapid iteration on experiments for evaluating new hardware prototypes, data collection improvements, and to gain understanding of key aspects of our system.
• Develop analytical tools for visualizing and understanding data quality.
• Work with hardware and electrical engineers to improve the overall sensing stack.
Requirements:
• PhD in neuroscience, biomedical engineering, machine learning, computer science, or related fields (or equivalent industry experience).
• Fluency in Python and PyTorch.
• Ability to collaborate effectively across different teams and rapidly adapt to new fields.
• Experience with dimensionality reduction techniques and time series data analysis.
• Independent work ethic, flexibility, and resourcefulness.
• Effective communication and collaboration skills.
• Comfortable in fast moving startup environment, excited to build independently
Preferred Qualifications:
• Strong familiarity with real-time human-machine interaction, ranging from automatic speech recognition to closed-loop neural interfaces.
• Expertise with motor control, communication prostheses, and/or speech neuroscience.
• Worked on consumer wearable devices.
• Machine learning infrastructure familiarity: experiment management tracking (e.g. Hydra, WandB, Neptune) and AWS/GCP
Details:
• This position is full time, on-site in San Francisco (SOMA)
• Company size: 10-20 people
Other keywords: Data science, speech recognition, dimensionality reduction, applied science
About Greylock:
Greylock is an early-stage investor in hundreds of remarkable companies including Airbnb, LinkedIn, Dropbox, Workday, Cloudera, Facebook, Instagram, Roblox, Coinbase, Palo Alto Networks, among others. More can be found about us here: https://greylock.com/
About the Greylock Recruiting Team:
As full-time, salaried employees of Greylock, we provide free candidate referrals/introductions to active and upcoming investments to help them grow/succeed (as one of the many services we provide). Our recruiting team, combined, has over 125 years of in-house recruiting experience at successful startups through FAANG’s and over 30 years of VC Talent.
