Job Description
Are you ready to define the future of human-computer interaction? Nexus Future Systems is on a mission to pioneer the seamless integration of Artificial Intelligence and human cognition by 2026. We are seeking a visionary Senior AI & Neural Interface Architect to lead our breakthrough research in Brain-Computer Interfaces (BCI) and advanced machine learning models.
In this high-impact role, you will bridge the gap between neuroscience and software engineering, designing the neural architectures that will power the next generation of human-AI symbiosis. You will work in a state-of-the-art facility, collaborating with elite neuroscientists and quantum computing experts. If you are passionate about pushing the boundaries of what is possible and want to build the infrastructure for the year 2026, we want to hear from you.
Why Join Us?
- Shape the Future: Directly influence the roadmap for next-gen neural interfaces.
- Premium Compensation: Competitive salary and equity package reflecting your senior expertise.
- Elite Team: Work alongside PhDs and industry leaders in a collaborative, innovation-first culture.
- Flexible Environment: Hybrid work model with access to our advanced R&D lab in downtown San Francisco.
Responsibilities
- Design and architect scalable neural network models specifically tuned for low-latency BCI data streams.
- Collaborate with neuroscientists to translate biological signals into actionable machine learning inputs.
- Optimize inference engines for edge devices and wearable neural headsets.
- Implement rigorous data privacy protocols to ensure the security of sensitive neural data.
- Lead code reviews and mentor junior engineers in deep learning and signal processing.
- Publish research findings and present technical roadmaps to executive stakeholders.
Qualifications
- Master’s or PhD in Computer Science, Neuroscience, Electrical Engineering, or a related field.
- Minimum of 5 years of professional experience in Deep Learning, NLP, or Reinforcement Learning.
- Proven expertise in Python, C++, and TensorFlow or PyTorch frameworks.
- Experience with signal processing libraries (e.g., SciPy, OpenCV) and real-time data processing.
- Strong understanding of neural architecture search and model compression techniques.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.