Job Description
Are you ready to architect the intelligence of tomorrow? Quantum Horizon Labs is pioneering the next evolution of generative AI, and we are seeking a visionary Lead AI Architect to define our infrastructure for the 2026 era.
In this role, you will bridge the gap between theoretical AI research and production-grade scalability. You will lead a world-class team in deploying autonomous agents and optimizing neural networks for real-time decision-making. If you are passionate about the future of technology and want to build systems that redefine human-machine interaction, we want to meet you.
Why join us?
- Work with state-of-the-art LLMs and Transformer architectures.
- Shape the roadmap for autonomous systems.
- Competitive equity package and top-tier benefits.
Responsibilities
- Architectural Leadership: Design and implement scalable, fault-tolerant AI infrastructure capable of handling high-throughput inference workloads.
- Research Translation: Translate cutting-edge academic research in Deep Learning into production-ready software components.
- Model Optimization: Lead initiatives in model compression, quantization, and edge deployment to ensure efficiency across diverse hardware.
- Team Mentorship: Mentor senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Strategic Vision: Define the technical roadmap for AI integration within our core product suite for the 2026 fiscal year.
- Performance Tuning: Continuously monitor and optimize model latency and accuracy metrics.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on Machine Learning/AI systems architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and C++.
- Cloud Expertise: Deep experience deploying models on AWS, GCP, or Azure using Kubernetes and Docker.
- Algorithm Knowledge: Strong understanding of NLP, Reinforcement Learning, and distributed systems.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.