Applied AI Scientist, Language & Context for BCI

echo inc.; San Francisco (CA); On-site; USD 180,000 - 230,000; Full time

Benefits offered by this job

Stock options

Comprehensive benefits package

401(k) program with matching

Job summary

Echo Neurotechnologies in San Francisco seeks an experienced Applied AI Scientist focused on language and context modeling to advance Brain-Computer Interface applications. You will design, fine-tune, personalize, and miniaturize flexible models for real-world patient impact.

Join a small, cross-functional team to develop real-time pipelines, deploy LM models, and contribute to documentation and quality processes.

Qualifications

• Bachelor's or Master’s in math, engineering, data science, or related quantitative field.
• At least 5 years of combined academic and professional ML experience.
• Experience deploying ML models in industry.
• Experience designing, training, and evaluating transformers.

Responsibilities

• Develop language modeling solutions for brain-computer interface applications.
• Design real-time ML pipelines with multi-input streams.
• Deploy state-of-the-art models for parsing audio, video, and application states.
• Miniaturize models for low-latency processing.
• Collaborate in a small cross-functional team to hit R&D and product goals.
• Maintain clear, well-documented code, analysis pipelines, and results.
• Contribute to documentation for ML-related Quality Management System.

Skills

Python

PyTorch

Transformer models

Reinforcement learning

Multilingual modeling

Time-series data

Education

Bachelor's or Master’s in quantitative field

Tools

GPU toolkits

Job description

Echo Neurotechnologies in San Francisco seeks an experienced Applied AI Scientist focused on language and context modeling to advance Brain-Computer Interface applications. You will design, fine-tune, personalize, and miniaturize flexible models for real-world patient impact.

Join a small, cross-functional team to develop real-time pipelines, deploy LM models, and contribute to documentation and quality processes.