Job Description
Are you ready to define the future of Artificial Intelligence? Chronos Dynamics is seeking a visionary Lead AI Architect to spearhead Project 2026—our ambitious initiative to engineer the world's most advanced predictive reasoning engine. In this role, you will build the foundational neural architectures that will drive the next generation of temporal intelligence and decision-making systems.
We are not just building software; we are crafting the blueprint for the future. If you are a top-tier engineer passionate about pushing the boundaries of what is possible in machine learning and distributed systems, we want to hear from you.
Why Join Us?
- Work on the most complex AI challenges of the decade.
- Competitive compensation package and equity options.
- Flexible remote-first policy with a hub in the heart of SF.
- Access to cutting-edge hardware and proprietary datasets.
Responsibilities
- Architect and deploy scalable, fault-tolerant neural networks capable of processing multi-dimensional temporal data.
- Lead the research and development of proprietary machine learning models for Project 2026, focusing on predictive analytics and autonomous decision loops.
- Collaborate with cross-functional teams of data scientists, engineers, and product managers to translate abstract concepts into production-ready code.
- Mentor junior engineers and conduct code reviews to maintain high engineering standards.
- Optimize model performance for low-latency inference in high-stakes environments.
- Stay ahead of industry trends in AI safety, ethics, and advanced architectures.
Qualifications
- PhD or Master’s degree in Computer Science, Physics, Mathematics, or a related quantitative field.
- 10+ years of professional experience in software engineering, with at least 5 years specifically in AI/ML architecture.
- Deep proficiency in Python, PyTorch, or TensorFlow, and experience with distributed computing frameworks (Kubernetes, Spark).
- Proven track record of deploying large-scale machine learning models in production environments.
- Strong understanding of deep learning architectures, attention mechanisms, and generative models.
- Excellent problem-solving skills and the ability to thrive in a fast-paced, innovative startup culture.