SUMMARY

We are seeking an experienced Applied AI Scientist, with a focus on language & context modeling, to join our team. The person who fills this role will apply ML/AI principles and practices to designing, developing, fine-tuning, personalizing, and miniaturizing flexible language and context models for use within brain-computer interface applications to have real-world impact on patients with physical disabilities.

PRIMARY ROLE AND RESPONSIBILITIES

• Language modeling
  • Leverage a deep understanding of LMs to create custom solutions for brain-computer interface applications, including LLM fine-tuning, customization, and dissection
  • Explore a variety of LM strategies of various scales and complexities for tailored integration into other decoding pipelines
  • Characterize agentic AI tools for suitability in product user interfaces
• Context modeling
  • Design and build ML pipelines capable of performing flexible, real-time inference with multiple input streams
  • Deploy custom or off-the-shelf state-of-the-art models for parsing audio, video, and application states
  • Perform context engineering to aggregate and model contextual information for use in downstream decoders
• General ML practices & company standards
  • Model dissection and interpretability to extract information-rich latent representations from large models (e.g. pretrained foundation models) for broad and generalized use in other models
  • Model miniaturization for low-latency and computationally inexpensive processing
  • Work collaboratively and effectively within a small, cross-functional team to hit both R&D and product-focused goals
  • Maintain versioned, clear, and highly documented code, analysis pipelines, and results for maximum interpretability and reproducibility
  • Contribute to documentation for a Quality Management System, as appropriate and relevant to ML implementations that become part of medical products

QUALIFICATIONS

• Bachelor's or Master's degree in Math, Engineering, Data Science, or other relevant quantitative field
• A minimum of 5 years of combined academic and professional ML experience
• Experience deploying ML models in an industry setting
• Experience designing, developing, and deploying LM models in an industry setting
• Experience designing, training, and evaluating transformers
• Proficiency in Python and PyTorch
• Proficiency in using GPUs and GPU software toolkits to accelerate ML pipelines

OTHER QUALIFICATIONS

• Experience working with reinforcement learning, LLM alignment and safety, and multilingual modeling
• Experience developing foundation models and applying transfer-learning techniques
• Experience working with high-dimensional time-series datasets
• Experience working on medical or clinical applications
• Experience translating methods described in scientific publications to available datasets
• Experience working with speech-recognition, video-processing, and application-parsing models