Job Description
Welcome to the future. Nexus Future Labs is pioneering the technological landscape of 2026, building the infrastructure for the next generation of artificial general intelligence (AGI) and quantum-computing integration. We are seeking a visionary Senior AI Systems Architect to lead our core infrastructure team.
In this pivotal role, you will bridge the gap between theoretical AI breakthroughs and scalable, high-performance production systems. You will architect the neural network frameworks that power autonomous agents, ensuring they are robust, efficient, and ready for the demands of a decentralized, quantum-enhanced world.
Why Join Us?
- Shape the trajectory of technology in 2026 and beyond.
- Work with a world-class team of quantum physicists and data scientists.
- Competitive compensation and equity packages.
Responsibilities
- Architect Scalable AI Infrastructure: Design and implement the core distributed systems architecture for our next-gen AI models, optimizing for low-latency and high-throughput.
- Quantum-Neural Integration: Lead the development of hybrid algorithms that leverage quantum processing units (QPUs) alongside traditional GPUs to accelerate training loops.
- System Optimization: Continuously monitor, profile, and optimize the inference pipeline to ensure real-time decision-making capabilities for autonomous fleets.
- Technical Leadership: Mentor junior architects and engineers, conducting code reviews, and establishing best practices for cloud-native AI deployment.
- Strategic Roadmapping: Collaborate with the CTO to define the technical roadmap for 2026, evaluating emerging technologies like neuromorphic computing.
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Physics, or a related field, with a focus on Artificial Intelligence or Quantum Computing.
- Experience: 10+ years of experience in software architecture, with at least 5 years specifically focused on Large Language Models (LLMs) or Deep Learning systems.
- Technical Stack: Proficiency in Python, C++, and Rust. Experience with frameworks such as PyTorch, TensorFlow, and quantum SDKs like Qiskit or Cirq.
- Cloud Mastery: Deep expertise in AWS, Google Cloud Platform, or Azure, specifically regarding GPU instances and serverless AI functions.
- Problem Solving: Demonstrated ability to solve complex, high-scale performance bottlenecks in distributed environments.