Senior Data Platform Architect (BCI & Neuroscience) at Synchron

New York, New York, United States -

Full Time

Start Date

Immediate

Expiry Date

23 Mar, 26

Salary

210000.0

Posted On

23 Dec, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Platform Architecture, Python, Scientific Computing, Cloud Platforms, Distributed Compute, Performance Optimization, Data Management, Version Control, APIs, Linux, ML Frameworks, MLOps, Data Lake, Collaboration, Neuroscience, Biomedical Data

Industry

Medical Equipment Manufacturing

Description

About Synchron Synchron is a neurotechnology company with a mission to deliver the first commercially scalable brain-computer interface (BCI) for millions of people with paralysis to reconnect with the world. Our minimally invasive BCI system is designed to enable users to control digital devices directly through thought, restoring access and control over the digital world. Our team is working at the intersection of healthcare and technology to translate breakthrough research into real-world care. Join us in shaping a more connected and accessible future. 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 Benefits* Subsidized medical and dental insurance coverage for you and your dependent(s) Life insurance, short-term disability, long-term disability 401k Discretionary unlimited PTO Flexible Spending Account for you and your dependent(s), with eligible plan elections Commuter benefits for NY employees *for full-time, exempt employees Equal Employment Opportunity (EEO) Synchron is an equal opportunity employer. We are committed to creating an inclusive environment for all employees and applicants and provide equal employment opportunities without regard to race, color, religion, sex, pregnancy, sexual orientation, gender identity or expression, national origin, age, disability, genetic information, marital status, veteran status, or any other characteristic protected by applicable law. If you need a reasonable accommodation during the application or interview process, please let us know. Join Us At Synchron, you will be part of a transformative mission and you will work alongside driven people who believe in the power of collaboration and innovation to make a lasting impact. If you are excited to stretch your skills and contribute to something meaningful, apply and now and build the future with us.

Responsibilities

The Senior Data Platform Architect will lead the evolution of a modular, cloud-native platform for machine learning and real-time analytics in brain-computer interface applications. This includes defining architectural patterns, selecting technologies, and ensuring the platform supports scientific rigor and compliance.