Job Description
Are you ready to define the future of Artificial Intelligence?
Quantum Horizon Technologies is a pioneer in next-generation computing, and we are launching Project 2026 to revolutionize how humans interact with autonomous systems. We are seeking a visionary Lead AI Architect to lead our elite engineering squad in designing the neural architectures that will power the next decade of innovation.
In this high-impact role, you won't just write code; you will architect the brain of our next-generation products. If you are passionate about pushing the boundaries of what's possible in 2026 and beyond, we want to hear from you.
Why Join Us?
- Impact: Work on cutting-edge Agentic AI and Autonomous Systems.
- Compensation: Competitive salary and equity package.
- Environment: Collaborative, high-performance, and future-focused culture.
Responsibilities
- Architect Future-Proof AI Systems: Design and deploy scalable, high-performance neural networks and LLM architectures tailored for the 2026 landscape.
- Lead Technical Strategy: Define the technical roadmap for our AI initiatives, ensuring alignment with long-term business goals and emerging industry trends.
- Model Optimization: Drive the research and implementation of model compression, quantization, and edge deployment techniques for real-time applications.
- Team Leadership: Mentor a team of senior data scientists and ML engineers, fostering a culture of innovation and continuous learning.
- Cross-Functional Collaboration: Partner with product managers and engineering teams to translate complex research into production-ready features.
- Research & Development: Stay ahead of the curve in emerging technologies such as Neural Rendering, Reinforcement Learning, and Quantum AI integration.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of experience in software engineering with a strong focus on AI/ML.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Ray, Kubernetes).
- Architecture Skills: Proven track record of designing end-to-end AI systems, from data pipelines to model inference.
- Communication: Exceptional ability to communicate complex technical concepts to both technical and non-technical stakeholders.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and deliver creative, scalable solutions.