Job Description
Are you ready to define the technological landscape of 2026? Nexus Horizon Labs is seeking a visionary Senior AI & Quantum Systems Engineer to lead our next-generation research initiatives.
We are building the infrastructure for the future. Our mission is to integrate Artificial General Intelligence (AGI) with quantum computing paradigms, creating systems that are not only scalable but also ethically aligned. In this role, you won't just write code; you will architect the very fabric of next-gen computing.
Join a team of elite engineers and researchers dedicated to pushing the boundaries of what is possible. If you thrive in high-pressure environments and want to leave a legacy in the tech world, this is your opportunity.
Why Join Nexus Horizon Labs?
- Impactful Work: Directly contribute to the evolution of AGI and quantum solutions.
- World-Class Team: Collaborate with PhDs and industry veterans from top tech firms.
- Future-Proof Role: Position yourself at the forefront of the tech industry’s evolution.
Responsibilities
- Design and architect scalable, fault-tolerant systems integrating neural networks with quantum processors.
- Lead the development of proprietary algorithms for predictive modeling and autonomous decision-making.
- Collaborate with cross-functional teams to translate complex research concepts into production-ready software.
- Optimize deep learning models for edge computing environments and low-latency quantum hardware.
- Mentor junior engineers and conduct code reviews to ensure engineering excellence.
- Stay ahead of emerging trends in AI, machine learning, and quantum mechanics to inform architectural decisions.
Qualifications
- Master’s or PhD in Computer Science, Physics, Mathematics, or a related technical field.
- 8+ years of experience in software engineering, with at least 3 years in AI/ML or Quantum Computing.
- Proficiency in Python, C++, and Rust, with deep understanding of parallel computing.
- Hands-on experience with quantum computing frameworks (e.g., Qiskit, Cirq) and classical ML libraries (TensorFlow, PyTorch).
- Strong grasp of distributed systems, cloud architecture (AWS/GCP), and data pipeline management.
- Demonstrated ability to solve complex, unstructured problems with innovative technical solutions.