Job description

Company Overview Echo Neurotechnologies is an exciting new startup in the Brain-Computer Interface (BCI) space, driving innovation through advanced hardware engineering and AI solutions. Our mission is to deliver cutting-edge technologies that restore autonomy to people living with disabilities and improve their quality of life. Team Culture Join a small, dedicated team of knowledgeable and motivated professionals. Our early-stage environment offers the opportunity to take ownership of broad decisions with significant and long-lasting impact. We emphasize continuous learning and growth, fostering cross-functional collaboration where your contributions are vital to our success. 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 What We Offer An opportunity to work on exciting, cutting-edge projects to transform patients’ lives in a highly collaborative work environment. Competitive compensation, including stock options. Comprehensive benefits package. 401(k) program with matching contributions. Equal Opportunity Employer Echo Neurotechnologies is an Equal Opportunity Employer (EOE). We celebrate diversity and are committed to creating an inclusive environment for all employees. Confidentiality All applications will be treated confidentially. Applicants may be asked to sign an NDA after the initial stages of the interview process.

Requirements

Must-haves

Company Overview
Team Culture
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
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
Experience working with reinforcement learning, LLM alignment and safety, and multilingual modeling

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aimlllmpython

Platform: greenhouse
Effort: quick

Benefits

Benefits detected in the listing.

401(K)