Job Description
The Future of Intelligence Starts Here.
Horizon Dynamics is pioneering the next generation of artificial intelligence. We are seeking a visionary Lead AI Architect to design and deploy scalable machine learning systems that will redefine the industry landscape. In this role, you will bridge the gap between theoretical research and production-grade applications, ensuring our solutions are robust, ethical, and transformative.
Why Join Us?
- Impact: Work on cutting-edge projects that shape the future of technology.
- Compensation: Competitive salary and equity package.
- Environment: Collaborative, innovative culture in the heart of San Francisco.
Are you ready to architect the future? Apply today.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of complex machine learning infrastructure and scalable data pipelines.
- Model Development: Lead the research, development, and deployment of advanced AI models, including Large Language Models (LLMs) and computer vision systems.
- Team Mentorship: Guide a team of senior data scientists and engineers, fostering a culture of continuous learning and technical excellence.
- Strategic Planning: Translate business objectives into technical roadmaps and AI strategy, ensuring alignment with Horizon Dynamics' long-term goals.
- Performance Optimization: Continuously monitor model performance, reduce latency, and optimize resource utilization for high-traffic environments.
- Ethical AI: Ensure all AI systems adhere to ethical guidelines, data privacy standards, and regulatory compliance requirements.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field.
- Experience: 7+ years of professional experience in AI/ML engineering, with at least 3 years in a lead or architectural role.
- Technical Skills: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (e.g., Kubernetes, Docker).
- Domain Knowledge: Proven track record of deploying production-ready AI solutions in cloud environments (AWS, GCP, or Azure).
- Problem Solving: Strong ability to troubleshoot complex system issues and drive architectural decisions under pressure.
- Communication: Excellent verbal and written communication skills, with the ability to explain technical concepts to non-technical stakeholders.