Job Description
Are you ready to architect the future of intelligence?
Nexus Horizon Solutions is pioneering the Project 2026 initiative—a groundbreaking frontier in predictive AI and autonomous systems. We are looking for a visionary Lead AI Architect to design the infrastructure that will define the next decade of technological evolution.
In this role, you won't just maintain legacy systems; you will build them from the ground up. You will lead a team of elite engineers in developing self-improving algorithms capable of solving complex global challenges.
Why Join Us?
- Work on state-of-the-art generative models.
- Competitive equity package and top-tier benefits.
- Flexible remote-first culture with premium San Francisco amenities.
Responsibilities
- System Architecture: Design and implement scalable, fault-tolerant AI infrastructure tailored for high-volume data processing and real-time decision-making.
- Research & Development: Spearhead research into novel neural network architectures to advance the capabilities of Project 2026.
- Team Leadership: Mentor and manage a high-performance engineering team, fostering a culture of innovation and technical excellence.
- Strategic Planning: Define technical roadmaps and collaborate with product leadership to align AI capabilities with business objectives.
- Compliance: Ensure all AI systems adhere to ethical guidelines, data privacy regulations, and industry standards.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field; equivalent practical experience is highly valued.
- Technical Mastery: Deep expertise in Python, PyTorch, or TensorFlow with a proven track record of deploying production-grade ML models.
- Experience: 7+ years of experience in software engineering and machine learning, with at least 2 years in a lead or architectural capacity.
- Cloud Proficiency: Hands-on experience with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Exceptional ability to troubleshoot complex system failures and optimize for performance and latency.