Job Description
Are you a visionary engineer ready to define the future of artificial intelligence? Nexus Horizon Systems is seeking a visionary AI Architect (2026 Roadmap) to lead our next-generation research division. We are building the foundational infrastructure for the AI advancements expected to define the year 2026 and beyond.
In this pivotal role, you will bridge the gap between theoretical machine learning breakthroughs and scalable production systems. You will work closely with quantum computing researchers and data scientists to architect systems that are not only state-of-the-art today but future-proof for tomorrow.
Why join us?
- Work on cutting-edge projects that will influence global AI standards.
- Competitive equity package with a clear path to leadership.
- Flexible work environment in the heart of San Francisco's tech hub.
Key Responsibilities:
- Lead the architectural design and implementation of scalable AI infrastructure for the 2026 product roadmap.
- Design and optimize deep learning models for high-performance computing environments.
- Collaborate with cross-functional teams to integrate AI solutions into core products.
- Define technical standards and best practices for machine learning operations (MLOps).
- Research emerging AI paradigms and evaluate their feasibility for future deployment.
Qualifications:
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 7 years of experience in software engineering, with at least 3 years specifically in AI/ML architecture.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience with distributed systems, cloud platforms (AWS/GCP), and containerization (Docker/Kubernetes).
- Proven track record of deploying large-scale machine learning models into production environments.
- Exceptional problem-solving skills and ability to communicate complex technical concepts to diverse stakeholders.
Responsibilities
- Lead the architectural design and implementation of scalable AI infrastructure for the 2026 product roadmap.
- Design and optimize deep learning models for high-performance computing environments.
- Collaborate with cross-functional teams to integrate AI solutions into core products.
- Define technical standards and best practices for machine learning operations (MLOps).
- Research emerging AI paradigms and evaluate their feasibility for future deployment.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 7 years of experience in software engineering, with at least 3 years specifically in AI/ML architecture.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Experience with distributed systems, cloud platforms (AWS/GCP), and containerization (Docker/Kubernetes).
- Proven track record of deploying large-scale machine learning models into production environments.
- Exceptional problem-solving skills and ability to communicate complex technical concepts to diverse stakeholders.