Job Description
Architect the Future of Intelligence
Nexus Future Labs is pioneering the infrastructure required for the next generation of artificial general intelligence. We are seeking a visionary AI Systems Architect to lead our 2026 roadmap initiatives. In this role, you will bridge the gap between theoretical AI breakthroughs and scalable, production-grade systems that redefine industry standards.
Why Join Us?
- Work on cutting-edge technologies that will shape 2026 and beyond.
- Competitive compensation package with equity options.
- Flexible remote-first culture with quarterly in-person summits.
Key Responsibilities
- Design and implement high-performance distributed AI architectures capable of supporting the 2026 compute demands.
- Lead the migration to next-gen inference engines and optimize model serving latency.
- Collaborate with cross-functional teams to define technical roadmaps for autonomous agents.
- Ensure system scalability, fault tolerance, and security compliance across global data centers.
- Drive the adoption of emerging hardware accelerators (e.g., TPUs, NPUs) into core workflows.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 8+ years of experience in Systems Architecture, with a focus on Machine Learning or Deep Learning.
- Deep expertise in Python, Rust, and distributed systems (Kubernetes, gRPC).
- Proven track record of deploying Large Language Models (LLMs) at scale.
- Strong understanding of data pipelines, vector databases, and semantic search technologies.
Responsibilities
- Design and implement high-performance distributed AI architectures capable of supporting the 2026 compute demands.
- Lead the migration to next-gen inference engines and optimize model serving latency.
- Collaborate with cross-functional teams to define technical roadmaps for autonomous agents.
- Ensure system scalability, fault tolerance, and security compliance across global data centers.
- Drive the adoption of emerging hardware accelerators (e.g., TPUs, NPUs) into core workflows.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field.
- 8+ years of experience in Systems Architecture, with a focus on Machine Learning or Deep Learning.
- Deep expertise in Python, Rust, and distributed systems (Kubernetes, gRPC).
- Proven track record of deploying Large Language Models (LLMs) at scale.
- Strong understanding of data pipelines, vector databases, and semantic search technologies.