Job Description
Are you ready to architect the future of intelligent systems?
Quantum Horizon Labs is seeking a visionary Senior AI Architect (2026 Vision) to lead our research and engineering division. As we prepare for the next era of technological advancement, we need a technical leader who can bridge the gap between theoretical breakthroughs and scalable production environments. You will be responsible for designing the foundational AI infrastructure that will power our solutions well into 2026 and beyond.
In this high-impact role, you will work at the intersection of deep learning, distributed systems, and generative AI, pushing the boundaries of what is possible in the enterprise space.
Why Join Us?
- Work on cutting-edge Agentic AI and predictive modeling technologies.
- Competitive compensation package and equity opportunities.
- Flexible hybrid work environment in the heart of Austin's tech corridor.
- Access to state-of-the-art compute resources and research grants.
Responsibilities
- Design & Strategy: Lead the architectural design of next-generation AI models, focusing on scalability, efficiency, and ethical AI integration.
- R&D Leadership: Drive research initiatives focused on emerging paradigms such as Multi-Modal Learning and Autonomous Agent frameworks.
- System Optimization: Oversee the deployment and optimization of large-scale ML pipelines, ensuring sub-millisecond latency and high availability.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and security teams to translate business requirements into robust technical solutions.
- Technical Mentorship: Guide a team of junior engineers and data scientists, fostering a culture of continuous learning and innovation.
- Compliance & Safety: Implement rigorous testing and validation protocols to ensure model safety, fairness, and regulatory compliance.
Qualifications
- Education: Master’s or PhD in Computer Science, Machine Learning, or a related quantitative field.
- Experience: 7+ years of professional experience in software engineering, with at least 4 years specifically in AI/ML architecture.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, Ray, or Spark).
- Modeling: Proven track record of designing and deploying Large Language Models (LLMs) or Generative Adversarial Networks (GANs).
- Soft Skills: Exceptional communication skills with the ability to explain complex technical concepts to non-technical stakeholders.
- Problem Solving: Demonstrated ability to troubleshoot complex system bottlenecks and drive architectural decisions under tight deadlines.