Job Details

About The Company

Orbit is building the foundational AI Infrastructure for emotions. A read interface to human emotions will be the most consequential data layer, enabling empathetic AI and precision mental healthcare. It will fundamentally transform how we interact with each other and technology.

Backed by founders and operators of top AI labs, consumer hardware, pharma, and enterprise companies, and venture-backed.

About The Team We Are Building

We're building a generational founding team which is truly full-stack - from neural sensors to complex models. If you want to work on deep technological problems and help pioneer the future of NeuroAI, this is the place for you. Projects have opportunities for a high degree of autonomy and demand intense, fast-paced learning.

About You

• Strong fundamentals in software engineering with a track record of delivering robust, maintainable systems
• Comfortable working across the stack — from data pipelines and simulation tooling to user-facing applications
• Interested in real-time data processing, scientific computing, and working close to cutting-edge neuroimaging hardware
• Able to quickly learn new technologies, dive deep into unfamiliar problem spaces, and contribute in multiple areas
• Excited to learn neuroimaging and neuroscience context (we will support you in getting up to speed)
  
  

• BS or higher in Computer Science, Computer Engineering, Electrical Engineering, Mathematics or related STEM field; exceptional self-taught engineers also considered
  
  

• Experience building backend systems, APIs, or cloud-based infrastructure.
• Familiarity with real-time or high-throughput data processing pipelines.
• Exposure to scientific computing, data infrastructure, or simulation tooling.
• Experience with databases, distributed systems, or cloud deployment.
• Comfort working with Python, C/C++, and/or modern web frameworks.
  
  

• Experience with GPU acceleration, parallel computing, or HPC.
• Familiarity with neuroimaging, medical imaging, or other scientific data domains.
• Full-stack skills for building internal tools and user-facing applications.
• Interest in ML pipelines or model training workflows.