Job Description
Shape the Future of Intelligence. Are you ready to build the systems that will define the next decade? Nexus Horizon is seeking a visionary AI/Quantum Integration Engineer to bridge the gap between emerging quantum computing capabilities and scalable AI architectures. In 2026, the boundary between artificial intelligence and quantum mechanics will dissolve, and we need pioneers to lead this charge.
As a key member of our R&D division, you will architect the next generation of machine learning models optimized for quantum processors. You won't just be writing code; you will be defining the computational paradigms of the future. Join us in San Francisco and work on projects that have the potential to revolutionize cryptography, drug discovery, and complex system optimization.
Why Nexus Horizon?
- Work on cutting-edge technology that is 5-10 years ahead of the market.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a premium office in SF.
Responsibilities
- Architect Hybrid Systems: Design and implement hybrid algorithms that leverage classical machine learning techniques combined with quantum computing primitives to solve complex optimization problems.
- Model Optimization: Translate classical neural network architectures into quantum circuit models, optimizing for qubit coherence and gate fidelity.
- Infrastructure Development: Build and maintain scalable cloud-based environments for quantum simulation and training, utilizing providers like AWS Braket and Google Cloud Quantum.
- Prototyping: Rapidly prototype and test new quantum AI concepts using Python, Qiskit, and Cirq.
- Collaboration: Partner with data scientists and hardware engineers to define the roadmap for our quantum hardware-software integration.
- Mentorship: Guide junior developers and researchers on best practices in quantum programming and advanced AI engineering.
Qualifications
- Education: Master’s or PhD in Computer Science, Physics, Mathematics, or a related field, with a focus on Quantum Information Science or Machine Learning.
- Technical Skills: Proficiency in Python, C++, and Rust. Deep understanding of quantum programming frameworks such as Qiskit, Cirq, or PennyLane.
- Experience: Proven experience in developing and deploying machine learning models, preferably with exposure to quantum computing concepts.
- Mathematical Aptitude: Strong background in linear algebra, probability theory, and functional analysis.
- Cloud Experience: Familiarity with cloud infrastructure (AWS, GCP, or Azure) and containerization tools (Docker, Kubernetes).
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.