Job Description
The Opportunity
We are at the precipice of a technological revolution. Nexus Horizon Systems is seeking a visionary Lead AI Architect to spearhead our research and development roadmap for the 2026 era. In this role, you won't just be maintaining legacy systems; you will be architecting the infrastructure that powers the next generation of autonomous agents and generative intelligence.
Join us in defining the ethical, scalable, and transformative standards of Artificial Intelligence for the coming decade.
Why Join Us?
- Work on cutting-edge projects with a focus on Long-Term AI Safety and Scalability.
- Competitive compensation package including equity options.
- Flexible remote-first policy with a premium office environment in SF.
Key Responsibilities
- Architect and design the high-level system architecture for our 2026 roadmap, focusing on generative models and neural networks.
- Lead a cross-functional team of researchers, engineers, and data scientists to translate theoretical AI concepts into production-ready solutions.
- Define technical standards, best practices, and governance frameworks for AI deployment to ensure security and compliance.
- Drive innovation in optimization techniques to reduce computational costs and improve model latency.
- Mentor senior engineers and foster a culture of continuous learning and technical excellence.
Qualifications
- Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or PhD preferred.
- 10+ years of experience in software engineering, with at least 5 years in Machine Learning and AI systems architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale machine learning models in production environments.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Strong understanding of deep learning principles, natural language processing (NLP), and computer vision.
Responsibilities
- Architect and design the high-level system architecture for our 2026 roadmap, focusing on generative models and neural networks.
- Lead a cross-functional team of researchers, engineers, and data scientists to translate theoretical AI concepts into production-ready solutions.
- Define technical standards, best practices, and governance frameworks for AI deployment to ensure security and compliance.
- Drive innovation in optimization techniques to reduce computational costs and improve model latency.
- Mentor senior engineers and foster a culture of continuous learning and technical excellence.
Qualifications
- Bachelor’s degree in Computer Science, Mathematics, or a related field; Master’s or PhD preferred.
- 10+ years of experience in software engineering, with at least 5 years in Machine Learning and AI systems architecture.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of deploying large-scale machine learning models in production environments.
- Experience with cloud infrastructure (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Strong understanding of deep learning principles, natural language processing (NLP), and computer vision.