Job Description
We are on the precipice of a technological renaissance. In 2026, the boundaries between biological cognition and digital processing will dissolve. Nexus Horizon Labs is seeking a visionary Senior Neural Interface Engineer to architect the next generation of Brain-Computer Interface (BCI) systems that will define the human experience for the next decade.
You will not be building standard software. You will be designing the synaptic pathways that allow thought to become action in real-time. Our mission is to empower human potential through seamless, safe, and high-bandwidth neural integration. If you are driven by the challenge of merging neuroscience with advanced AI and you want to work in the heart of the tech capital, this is your opportunity.
Why join Nexus Horizon?
- Work on the cutting edge of neuro-prosthetics and consumer BCI.
- Competitive equity and top-tier compensation package.
- Collaborate with world-class neuroscientists and AI ethicists.
- Shape the regulatory and technical standards for the industry.
Responsibilities
- Neural Architecture Design: Develop and optimize low-latency communication protocols between biological neural networks and silicon processors for our next-gen headsets.
- Real-time Signal Processing: Implement advanced algorithms to filter, interpret, and translate neural signals into actionable digital commands with sub-millisecond latency.
- Safety & Compliance: Establish rigorous fail-safes and safety protocols to ensure user well-being and prevent signal interference or feedback loops.
- System Integration: Lead the integration of firmware and hardware components, working closely with mechanical and electrical engineers to refine the physical form factor.
- Prototyping & Testing: Spearhead the development of proof-of-concept prototypes and conduct extensive stress testing in simulated and real-world environments.
- Technical Leadership: Mentor junior engineers and define coding standards for the neural processing team, ensuring scalability and maintainability.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Electrical Engineering, Neuroscience, or a related field with a focus on signal processing.
- Experience: 7+ years of professional experience in embedded systems, deep learning, or biomedical engineering.
- Technical Stack: Proficiency in Python, C++, and CUDA. Experience with TensorFlow, PyTorch, or Keras applied to time-series data.
- Knowledge: Deep understanding of EEG, ECoG, or fNIRS hardware and signal analysis.
- Problem Solving: Demonstrated ability to troubleshoot complex real-time data processing issues under strict performance constraints.
- Communication: Excellent verbal and written skills for presenting complex technical concepts to non-technical stakeholders.