Job Description
Join the Architects of Tomorrow.
Quantum Horizons is pioneering the next generation of artificial intelligence systems. As we prepare for the 2026 release of our flagship 'Nexus' platform, we are seeking a visionary Senior AI Architect to lead our research and development efforts. You will define the architectural pillars that will power autonomous systems for the next decade.
In this high-impact role, you will bridge the gap between theoretical machine learning research and scalable production engineering. You will be responsible for designing the infrastructure that supports advanced generative models, ensuring ethical AI deployment, and mentoring a team of elite engineers.
Why Join Us?
- Work on cutting-edge AI infrastructure for the 2026 timeline.
- Competitive equity package and top-tier benefits.
- Remote-first culture with access to world-class tech stack.
Are you ready to shape the future? Apply today.
Responsibilities
- Architectural Leadership: Design and implement scalable, fault-tolerant AI infrastructure for the 2026 roadmap, utilizing microservices and cloud-native technologies.
- Model Optimization: Lead the research and deployment of Large Language Models (LLMs) and neural networks, optimizing for latency and inference costs.
- Technical Strategy: Define the long-term technical vision for our AI stack, evaluating emerging technologies like quantum-inspired algorithms.
- Team Mentorship: Mentor senior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Ethical AI: Implement and oversee governance frameworks to ensure AI outputs are fair, transparent, and safe.
- Cross-Functional Collaboration: Partner with product and engineering teams to translate complex AI capabilities into user-friendly features.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related field from a top-tier institution.
- Experience: 7+ years of experience in software engineering with a focus on AI/ML, specifically in designing large-scale distributed systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Kubeflow, MLflow).
- Leadership: Proven track record of leading technical teams through complex product lifecycles.
- Problem Solving: Exceptional ability to solve ambiguous problems and navigate the trade-offs between speed, quality, and cost.
- Communication: Excellent verbal and written communication skills for technical documentation and stakeholder presentations.