Job Description
Shape the Future of Intelligence. Nexus Horizons is at the forefront of the 2026 AI revolution. We are seeking a visionary AI Architect 2026 to design the foundational infrastructure for our next-generation Artificial General Intelligence systems. This is not just a job; it is a mission to redefine the boundaries of what machines can learn and create.
In this high-impact role, you will bridge the gap between theoretical AI breakthroughs and scalable, production-ready engineering. You will lead a team of elite engineers in deploying next-generation neural networks and ensuring our systems remain resilient and ethical in a rapidly evolving digital landscape.
Why Join Us?
- Work on cutting-edge AGI research and infrastructure.
- Competitive equity package and comprehensive benefits.
- Flexible remote-first culture with premium San Francisco office access.
- Access to state-of-the-art hardware and research tools.
Responsibilities
- Architectural Leadership: Design and implement scalable machine learning infrastructure capable of supporting next-generation AI models and AGI development.
- Performance Optimization: Engineer high-performance computing environments and optimize deep learning pipelines for maximum throughput and minimal latency.
- System Integration: Oversee the integration of AI models into consumer products and enterprise solutions, ensuring seamless user experiences.
- Technical Mentorship: Mentor a diverse team of data scientists and engineers, establishing coding standards and technical best practices for the future.
- Risk Management: Develop robust security protocols and ethical guidelines to govern AI deployment and mitigate systemic risks.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Mathematics, or a related technical field.
- Experience: 5+ years of experience in Machine Learning Engineering, AI Architecture, or Systems Design, with a focus on large-scale distributed systems.
- Technical Stack: Expert proficiency in Python, PyTorch, TensorFlow, or JAX; deep knowledge of CUDA and GPU optimization.
- Cloud Expertise: Proven experience architecting solutions on major cloud platforms (AWS, GCP, or Azure) with a focus on serverless and containerized workloads.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems and drive technical innovation in ambiguous environments.