Job Description
Are you ready to architect the intelligence layer of tomorrow?
Nebula Nexus is pioneering the next generation of autonomous systems. We are seeking a visionary Senior AI Systems Architect to spearhead the development of our proprietary neural infrastructure, designed to redefine human-machine interaction by 2026. If you thrive in cutting-edge environments and want to build the foundational technologies of the future, this is your opportunity to lead.
Why Join Us?
- Work on post-quantum secure AI frameworks.
- Shape the roadmap for next-gen autonomous agents and neural interfaces.
- Competitive compensation package including equity and health benefits.
Key Responsibilities:
- Design and implement scalable, fault-tolerant AI infrastructure capable of processing exabytes of data.
- Lead the integration of edge computing with cloud-based deep learning models to minimize latency.
- Architect robust security protocols for neural networks, ensuring resilience against future quantum threats.
- Collaborate with cross-functional teams to define technical strategies and best practices for AI model deployment.
- Mentor junior engineers and foster a culture of innovation within the engineering team.
- Optimize model inference times to support real-time decision-making systems.
Qualifications:
- Bachelor’s degree in Computer Science, Mathematics, or a related field (Master’s preferred).
- 7+ years of experience in software engineering, with at least 3 years focused on Machine Learning Systems and AI infrastructure.
- Deep expertise in Python, Rust, or C++.
- Proven experience designing distributed systems using Kubernetes, Docker, and microservices.
- Strong background in implementing Post-Quantum Cryptography (PQC) standards.
- Familiarity with high-performance computing (HPC) and GPU acceleration (CUDA, PyTorch, TensorFlow).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.
Responsibilities
- Design and implement scalable, fault-tolerant AI infrastructure capable of processing exabytes of data.
- Lead the integration of edge computing with cloud-based deep learning models to minimize latency.
- Architect robust security protocols for neural networks, ensuring resilience against future quantum threats.
- Collaborate with cross-functional teams to define technical strategies and best practices for AI model deployment.
- Mentor junior engineers and foster a culture of innovation within the engineering team.
- Optimize model inference times to support real-time decision-making systems.
Qualifications
- Bachelor’s degree in Computer Science, Mathematics, or a related field (Master’s preferred).
- 7+ years of experience in software engineering, with at least 3 years focused on Machine Learning Systems and AI infrastructure.
- Deep expertise in Python, Rust, or C++.
- Proven experience designing distributed systems using Kubernetes, Docker, and microservices.
- Strong background in implementing Post-Quantum Cryptography (PQC) standards.
- Familiarity with high-performance computing (HPC) and GPU acceleration (CUDA, PyTorch, TensorFlow).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.