Job Description
Are you ready to define the interface between human consciousness and digital evolution? Nexus Horizon Labs is pioneering the next generation of Brain-Computer Interfaces (BCI) and is seeking a visionary Lead Neural Interface Architect to join our elite San Francisco team.
In this pivotal role, you will bridge the gap between neuroscience, advanced AI, and hardware engineering. You won't just be writing code; you will be architecting the neural pathways of tomorrow, ensuring seamless, high-bandwidth communication between biological systems and cloud computing.
Why Join Us?
- Work on cutting-edge technology that defines the 2026 landscape.
- Competitive equity package and top-tier benefits.
- Collaborate with world-class neuroscientists and AI researchers.
We are looking for a thought leader who is obsessed with low-latency data transmission and user experience.
Responsibilities
- Architect Neural Pathways: Design the core software architecture for high-bandwidth Brain-Computer Interfaces, optimizing for minimal latency and maximum data throughput.
- Signal Processing: Develop advanced algorithms to interpret neural signals and translate them into actionable digital commands with high fidelity.
- Security & Privacy: Implement robust encryption protocols to protect neural data, ensuring compliance with emerging bio-privacy regulations.
- Hardware-Software Integration: Collaborate with hardware engineers to calibrate firmware and software stacks for next-gen neural probes.
- Prototyping & Testing: Lead the end-to-end testing cycle of prototype interfaces, gathering user feedback to refine the user experience.
- Cross-Functional Leadership: Mentor a team of junior developers and researchers, fostering a culture of innovation and ethical AI development.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Neuroscience, Electrical Engineering, or a related technical field.
- Experience: 5+ years of experience in software engineering, specifically with real-time systems or embedded systems.
- Technical Skills: Proficiency in Python, C++, and CUDA. Experience with machine learning frameworks (TensorFlow/PyTorch) applied to biological signal processing.
- Neuroknowledge: Strong understanding of neuroscience principles, particularly regarding brain signal acquisition and interpretation.
- Problem Solving: Demonstrated ability to solve complex, interdisciplinary engineering problems under pressure.