Restorative Neurotechnologies

QA Engineer

• Participate in ongoing implementation of the Quality Management System (QMS) in conformance with US FDA Quality System Regulations, ISO 13485, IEC 62304, IEC 60601 and IEC 62366-1 and other relevant standards.
• Support the product development team in creation of design history files (DHFs) including product requirements, software and hardware design specifications, design verification and validation test protocols and reports, risk management file, cybersecurity risk files, biocompatibility and sterilization validation deliverables, traceability matrices, etc.
• Guide and lead risk management activities, including failure modes and effects analysis (FMEA) and hazards analysis, in alignment with ISO 14971.
• Engage and collaborate with suppliers and support design, development and design transfer activities.
• Support and participate in internal and external audits, coordinating and providing documentation and evidence of compliance.
• Support root cause analysis for nonconformances, defects and CAPAs, issue management, management review and quality data analysis.
• Foster a collaborative environment, champion continuous improvement initiatives and promote a quality culture across the organization.

Senior Quality Engineer

Full-stack Engineer

• Develop high-quality medical applications in a variety of environments, including Rust on desktop, Python on servers, React on web, and others.
• Contribute to critical design decisions across device, client, and server components.
• Mentor team members and promote knowledge sharing across the organization.
• Work closely with other engineers and cross-functional teams to plan and build.
• Document architectural designs and key decision-making processes.
• Ensure compliance with medical software standards and regulations.
• Follow best practices to create and maintain reproducible, clear, and highly documented code.

Senior Full Stack Software Engineer

Research Scientist

• Performing feature exploration to find more information-rich and robust features in existing neural datasets.
• Probing neural encoding of behavior and external stimuli to inform model designs and training strategies.
• Designing and assessing neural-control strategies for optimal co-adaptation / learning within brain-computer interface applications.
• Working collaboratively within a small team to develop and assess neural-decoding models and translate scientific findings into product implementations.
• Maintaining versioned, clear, and highly documented code, analysis pipelines, and results for maximum interpretability and reproducibility.

AI Research Scientist

• Leveraging a deep understanding of LMs to create custom solutions for brain-computer interface applications, including LLM fine-tuning, customization, and dissection.
• Exploring a variety of LM tokenizations and embeddings for better integration into other decoding pipelines.
• Working collaboratively within a small team to iterate on models and integrate LMs into product applications.
• Developing lightweight LMs, sequence-decoding algorithms, and other approaches for portable model deployment.
• Characterizing agentic AI tools for suitability within product applications.
• Maintaining 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.

Applied AI Scientist, Language Modeling

Backend Engineer

• Design and implement a robust server-side system architecture in a public cloud environment.
• Build APIs, data pipelines, and secure storage layers.
• Contribute to critical system design decisions affecting device and client software.
• Document architectural designs and key decision-making processes.
• Ensure compliance with medical software standards and regulations.
• Follow coding best practices to create and maintain reproducible, clear, and highly documented code.

Backend Software Architect – Python

Backend Software Engineer – Python

Data Engineer

• Design and build databases for massive-scale storage of heterogeneous and high-dimensional data and metadata
• Design and develop systems for high-throughput data ingestion, pipelining, curation, and quality assessments
• Characterize data throughput, efficiency, compressibility, and performance
• Provide observability, monitoring, and logging for data pathways
• Work collaboratively within a small team to integrate data platforms with research and product use cases
• Ensure compliance with medical software standards and regulations.
• Follow coding best practices to create and maintain reproducible, clear, and highly documented code.

Hardware Engineer

• Collect product requirements and design inputs from various teams, and translate them to firmware needs
• Develop firmware (and accompanying software) that meets product requirements and complies with FDA development standards
• Collaborate with electrical, hardware, and software engineers in creating sophisticated medical devices
• Design and implement firmware testing plans for verification/validation purposes
• Create documents describing firmware architectures

Firmware Engineer

Designer

• Design and iterate on core user flows for a complex software application.
• Specify UI/UX details across the entire product experience.
• Create and maintain a cohesive design system.
• Work cross-functionally to understand trade-offs across product, hardware, software, clinical and regulatory needs.
• Ensure compliance with relevant medical software standards and regulations.
• Document design choices and key decision-making processes.

Interaction Designer

• Modeling brain data and associated metadata to obtain insights into existing and future datasets and implement high-performance inference and translation pipelines
• Designing and creating state-of-the-art transformers and other ML models to decode brain signals into control signals for digital devices
• Keeping up with the latest AI techniques and being able to quickly assess the relevance and utility of these techniques, including with prototypical evaluations with company datasets
• Working collaboratively within a small team to explore and iterate on models, design the company's data-science platforms, and integrate ML models into product applications
• Maintaining 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