Job Description
We are pioneering the technology stack for the year 2026, building the foundational AI infrastructure required for autonomous systems and advanced neural interfaces. We are seeking a visionary Lead AI Infrastructure Engineer to join our elite engineering team in San Francisco.
In this role, you will not just maintain existing systems; you will architect the frameworks that will power the next generation of human-machine interaction. You will work at the intersection of quantum computing readiness, generative AI, and high-throughput data processing.
Why Nexus Horizon?
- Work on projects that define the roadmap for 2026 and beyond.
- Competitive compensation package including equity options.
- Flexible remote-first culture with premium co-working spaces.
Responsibilities
- Architect Scalable Systems: Design and implement high-availability, distributed machine learning pipelines capable of processing exabytes of data.
- Optimize Inference: Engineer edge-compliant models that run efficiently on decentralized hardware with minimal latency.
- Quantum-Ready Prep: Collaborate with quantum researchers to create hybrid classical-quantum algorithms for next-gen data processing.
- Model Governance: Implement rigorous testing frameworks and ethical AI compliance standards for generative models.
- Team Leadership: Mentor junior engineers and drive technical best practices across the infrastructure team.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 5+ years of professional experience in software engineering and machine learning infrastructure.
- Core Skills: Proficiency in Python, PyTorch, and Rust; extensive experience with Kubernetes and Docker.
- Knowledge: Deep understanding of transformer architectures and large language model (LLM) optimization techniques.
- Problem Solving: Proven track record of solving complex performance bottlenecks in distributed systems.