Job Description
We are at the precipice of a technological revolution. Nexus Horizon Technologies is seeking a visionary Senior AI Architect to lead the strategic design and implementation of our infrastructure for the year 2026 and beyond. You won't just be maintaining legacy systems; you will be building the foundation for the next generation of artificial intelligence.
In this role, you will bridge the gap between theoretical machine learning models and production-grade systems. You will define the technical roadmap, ensuring our platform scales efficiently to meet the demands of a rapidly evolving digital landscape. If you are passionate about the future and possess the expertise to architect resilient, scalable AI ecosystems, we want to hear from you.
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 hub in the heart of San Francisco.
- Access to top-tier hardware and research resources.
Responsibilities
- Lead the 2026 Roadmap: Define and execute the technical strategy for AI infrastructure, identifying emerging technologies to integrate for future readiness.
- System Architecture: Design scalable, fault-tolerant distributed systems capable of handling massive data throughput and complex computations.
- Model Deployment: Oversee the deployment, monitoring, and optimization of machine learning models in production environments (MLOps).
- Code Review & Standards: Establish and enforce high coding standards, conducting rigorous code reviews to ensure security and performance.
- Stakeholder Collaboration: Partner with product managers, data scientists, and engineering leads to translate business goals into technical solutions.
- Performance Tuning: Continuously analyze system bottlenecks and implement optimizations to improve latency and throughput.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on AI/ML infrastructure.
- Programming: Proficiency in Python, Rust, or Go, with deep knowledge of data structures and algorithms.
- Frameworks: Strong experience with ML frameworks (TensorFlow, PyTorch) and orchestration tools (Kubernetes, Docker).
- Cloud Expertise: Demonstrated experience architecting solutions on major cloud platforms (AWS, GCP, or Azure).
- Problem Solving: Ability to troubleshoot complex issues in a high-pressure environment and deliver robust solutions.