Senior Data Platform Architect (BCI & Neuroscience)

Role Overview 

We are seeking a hands-on Senior Data Platform Architect to lead the evolution of a modular, cloud-native platform that powers machine learning, calibration, and real-time analytics for a brain–computer interface (BCI). This role sits at the intersection of AI infrastructure, scientific computing, and neuroscience, enabling data scientists and neuroscientists to train, validate, and deploy models on complex, high-dimensional biomedical data. 

You will define architectural patterns, select technologies, and build critical platform components that make advanced ML and scientific workflows scalable, reproducible, and secure. 

What You’ll Do 

Platform & Architecture Leadership 

• Architect and evolve a modern AI/data platform (lakehouse, modular services, ML infrastructure) supporting large-scale neural and biomedical datasets (time-series, n-D arrays, metadata-rich experimental data). 

• Design end-to-end data and model lifecycles—from ingestion and curation to training, evaluation, deployment, and monitoring. 

• Define architectural standards for interoperability, performance, and scientific reproducibility. 

Scientific Collaboration 

• Partner closely with data scientists, neuroscientists, and clinicians to translate experimental needs into scalable technical solutions. 

• Ensure the platform supports exploratory research, rapid iteration, and production-grade deployment without compromising scientific rigor. 

• Read and reason about scientific literature, experimental protocols, and data limitations. 

Data Governance, Security & Compliance 

• Design privacy-first architectures aligned with FAIR principles and biomedical data regulations. 

• Implement data contracts, lineage, metadata management, and secure access controls for sensitive neural data. 

• Ensure compliance with applicable regulatory practices. 

• Maintain adherence to Zero Trust Architecture (ZTA) principles. 

Innovation & Technical Leadership 

• Evaluate emerging technologies, run POCs, and define a forward-looking platform roadmap. 

• Mentor engineers and scientists on platform usage, best practices, and architectural principles. 

• Act as a technical authority and evangelist for scalable AI and data systems. 

What You Bring 

Core Expertise 

• 8–12+ years in data platform architecture roles. 

• Strong experience with Python, numerical n-D arrays, and scientific computing workflows. 

• Deep familiarity with cloud platforms (AWS, GCP, or Azure) and cloud-native design. 

• Experience designing systems for distributed compute, GPUs, and performance optimization. 

• Solid understanding of data management principles, version control (Git), APIs, and Linux environments. 
• Bachelor's degree in a related field. 

AI & Data Platform Experience 

• Hands-on experience with ML frameworks (PyTorch, TensorFlow) and MLOps tooling. 

• Familiarity with data lake/lakehouse concepts, metadata systems, and large-scale data integration. 

• Experience enabling collaboration between research and production ML environments. 

Domain & Mindset 

• Ability to understand and reason about neuroscience or biomedical data  

• Strong architectural judgment, curiosity, and ability to learn new tools quickly. 

• Clear communicator who thrives in highly interdisciplinary teams. 

Why This Role Is Different 

• You will design the platform, not just pipelines. 

• Your primary customers are scientists and ML researchers 

• You will shape how neural data and AI models move from experiment to clinical-grade systems. 

• Your work directly impacts the future of brain–computer interfaces. 

Location: NYC (Specifically-Brooklyn) (In Person) 

Compensation: $170,000 – $210,000 base + equity + benefits