Job Description
We are seeking a visionary Senior AI Architect to join our elite '2026 Visionary' program. As the technology landscape accelerates toward the next generation of generative intelligence, we need a leader who can architect the systems that will define the future. This is a rare opportunity to work on cutting-edge AI infrastructure, ethical AI frameworks, and scalable machine learning models.
In this role, you will bridge the gap between theoretical research and production-grade engineering. You will be responsible for designing robust AI ecosystems that can handle the demands of 2026 and beyond.
Why Join Us?
- Work on the technology of tomorrow, today.
- Competitive equity package and performance bonuses.
- Flexible remote-first policy with premium office amenities in San Francisco.
- Access to top-tier compute resources and research collaboration.
Responsibilities
- Architect AI Solutions: Design and deploy scalable machine learning architectures for large-scale generative AI applications and autonomous agents.
- Optimize Performance: Implement advanced optimization techniques to improve inference speed and reduce latency in real-time AI systems.
- Ethical AI Oversight: Establish and enforce guidelines for responsible AI development, ensuring fairness, transparency, and safety in model outputs.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning within the engineering team.
- Research Integration: Translate cutting-edge research papers into practical, production-ready code and infrastructure.
- System Scalability: Ensure AI infrastructure can scale seamlessly to handle increasing data loads and user traffic.
Qualifications
- Experience: 5+ years of professional experience in software engineering and machine learning, with at least 2 years in a senior or lead architect role.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Kubernetes, Ray).
- Model Optimization: Deep understanding of model compression, quantization, and inference optimization techniques.
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Problem Solving: Exceptional ability to solve complex technical challenges and troubleshoot large-scale system issues.
- Communication: Excellent verbal and written communication skills with the ability to articulate complex technical concepts to non-technical stakeholders.