Job Description
Are you ready to define the future of human-computer interaction?
Stratosphere Systems is pioneering the next generation of neural interfaces. We are seeking a visionary Lead AI Architect to spearhead the development of our 2026 roadmap, bridging the gap between biological cognition and silicon processing. If you thrive in high-stakes, cutting-edge environments and want to build systems that change the world, we want you on our team.
Why join us?
- Impact: Directly influence the architecture of next-gen Brain-Computer Interfaces (BCI).
- Innovation: Work with state-of-the-art quantum-accelerated machine learning models.
- Culture: A diverse, elite team of engineers and ethicists pushing boundaries.
As a Lead AI Architect, you will be the technical authority responsible for designing scalable, low-latency AI models that power our wearable neural devices. You will guide a team of researchers and engineers, ensuring our solutions are not only powerful but also ethically sound and human-centric.
Responsibilities
- Architect and implement advanced neural network architectures optimized for real-time brain-computer interaction.
- Lead the technical strategy for the 2026 product roadmap, integrating quantum computing principles into classical ML pipelines.
- Conduct rigorous testing and validation of AI models to ensure high accuracy and minimal cognitive load for end-users.
- Mentor junior engineers and data scientists, fostering a culture of continuous innovation and technical excellence.
- Collaborate with bio-engineers and UX designers to translate biological signals into intuitive digital commands.
- Ensure data privacy and ethical AI compliance across all deployed neural interfaces.
Qualifications
- Master’s or PhD in Computer Science, Neuroscience, or a related field with a focus on Artificial Intelligence.
- 10+ years of experience in software engineering, with at least 5 years in a Lead Architect or Principal Engineer role.
- Deep expertise in Python, PyTorch, TensorFlow, and experience with quantum computing frameworks (Qiskit, Cirq).
- Proven track record of deploying scalable machine learning models in production environments.
- Strong understanding of signal processing, pattern recognition, and cognitive science principles.
- Excellent communication skills, with the ability to translate complex technical concepts to diverse stakeholders.