Job Description
Are you ready to shape the future of technology? Nexus Horizon Labs is seeking a visionary Senior AI & Quantum Architect to lead our Class of 2026 initiative. We are building the next generation of adaptive intelligence systems that bridge the gap between classical computing and quantum mechanics. This is a rare opportunity to define the roadmap for the next decade of technological evolution.
In this pivotal role, you will architect scalable machine learning models and quantum algorithms that solve complex, unsolved problems in real-time data processing and autonomous decision-making. You will work at the intersection of cutting-edge research and production-grade engineering, collaborating with top-tier researchers and engineers to deploy AI solutions that redefine industry standards.
Why join Nexus Horizon Labs?
- Work on the forefront of the 2026 technological revolution.
- Competitive compensation package including equity and bonuses.
- Flexible remote-first hybrid work culture.
- Access to state-of-the-art computing resources and research grants.
If you are a thought leader who thrives in ambiguity and wants to leave a lasting impact on the tech landscape, we want to meet you.
Responsibilities
- Design and implement next-generation neural network architectures optimized for quantum processors.
- Lead the end-to-end lifecycle of AI product development, from prototype to production deployment.
- Collaborate with cross-functional teams (Data Science, Engineering, Product) to define the Class of 2026 roadmap.
- Optimize existing models for speed, accuracy, and resource efficiency on distributed systems.
- Conduct rigorous testing and validation to ensure system reliability and ethical AI compliance.
- Mentor junior engineers and foster a culture of continuous learning and innovation.
Qualifications
- PhD or Master’s degree in Computer Science, Physics, Mathematics, or a related technical field.
- 5+ years of professional experience in AI/ML engineering, with at least 2 years in quantum computing or advanced AI research.
- Proficiency in Python, TensorFlow, PyTorch, and quantum programming languages (e.g., Qiskit, Cirq).
- Deep understanding of classical machine learning algorithms and their application to quantum problems.
- Strong background in distributed systems, cloud infrastructure (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to diverse stakeholders.