What are the responsibilities and job description for the Multimodal Machine Learning Scientist position at Greylock?
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 Description :
As a Multimodal Machine Learning Scientist, you will develop cutting-edge AI models to integrate and decode complex, multimodal data streams from our custom sensing hardware. You’ll play a pivotal role in advancing our silent speech technology stack by building and optimizing models for real-time applications. This position spans foundational research in deep learning, hands-on model development, and applying algorithms to scale across diverse data sources and users.
Responsibilities :
- Design and implement state-of-the-art machine learning algorithms for processing multimodal bio-signals, including time series, spatial, and spectral data.
- Build and optimize neural network architectures ranging from transformers to state space models.
- Develop and evaluate multimodal learning techniques to fuse information from multiple sensor modalities.
- Iterate rapidly on model prototypes for real-time inference on custom hardware.
- Create and maintain a robust evaluation framework for benchmarking model performance across datasets and participants.
- Collaborate closely with a diverse team, including hardware engineers, neuroscientists, and product designers, to align models with user needs.
Requirements :
Preferred Qualifications :
Details :
Other Keywords : deep learning, speech recognition, foundation models, real-time inference, data fusion, transformers, bio-signals, 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 :
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.
