Job Description
Shape the Future of Intelligence
Chronos Systems is pioneering the technological landscape of 2026. We are seeking a visionary Senior AI Architect to lead the development of our flagship generative AI ecosystem. In this role, you will bridge the gap between theoretical machine learning breakthroughs and scalable, production-grade software solutions. You will define the architectural standards for our next-generation neural networks, ensuring they are robust, ethical, and capable of solving complex global challenges.
Why Join Us?
- Work on cutting-edge AI projects that define the industry standard for 2026.
- Competitive equity package and top-tier health benefits.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to the latest hardware and cloud infrastructure.
Responsibilities
- Architect & Develop: Design and implement scalable AI infrastructure, focusing on Large Language Models (LLMs) and multi-modal neural networks for the 2026 roadmap.
- Optimization: Lead initiatives to optimize model inference latency and reduce computational costs in high-traffic environments.
- Ethical AI: Establish and enforce strict guidelines for AI bias, transparency, and safety within our autonomous systems.
- Technical Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Collaboration: Partner with product managers and engineering teams to integrate AI capabilities seamlessly into user-facing products.
- Research: Stay ahead of the curve by researching emerging technologies in Generative AI and Quantum Computing applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 5+ years of professional experience in Machine Learning, Deep Learning, or AI Engineering.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, and experience with MLOps tools (Docker, Kubernetes, MLflow).
- Specialization: Deep understanding of transformer architectures, reinforcement learning, and NLP pipelines.
- Communication: Exceptional ability to translate complex technical concepts into clear strategic directions for non-technical stakeholders.
- Certifications: Professional certification in AI/ML (e.g., Google Professional Machine Learning Engineer) is a plus.