Job Description
Are you ready to build the systems of tomorrow? Nexus Future Systems is seeking a visionary Senior AI & Next-Gen Architect to lead our R&D division in San Francisco. In this pivotal role, you will bridge the gap between current deep learning models and the advanced computing paradigms required for 2026 and beyond. We are looking for a builder who thrives on complexity and wants to engineer the foundation of the next digital revolution.
As a key member of our elite engineering team, you will define the technical roadmap for our flagship AI products, ensuring they remain at the forefront of innovation. If you are passionate about the intersection of artificial intelligence, quantum computing, and scalable architecture, this is your opportunity to leave a lasting legacy.
Why Join Us?
- Work on cutting-edge projects that define the future of technology.
- Competitive compensation package and equity options.
- Flexible remote-first culture with a premium office in the heart of SF.
Responsibilities
- Architect and deploy scalable neural networks capable of processing real-time data streams with zero latency.
- Lead the research and implementation of Generative AI models tailored for enterprise automation.
- Collaborate with cross-functional teams to integrate advanced AI solutions into core product ecosystems.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Optimize existing codebases for performance, security, and scalability in cloud environments.
- Stay ahead of industry trends, specifically focusing on AGI (Artificial General Intelligence) readiness.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of professional experience in software engineering and machine learning architecture.
- Proficiency in Python, TensorFlow, PyTorch, and distributed computing frameworks.
- Deep understanding of cloud infrastructure (AWS, Azure, or GCP) and containerization (Docker, Kubernetes).
- Experience with large language models (LLMs) and prompt engineering techniques.
- Strong problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.