Job Description
Are you ready to define the technological landscape of 2026?
At Chronos Future Labs, we are not just building software; we are architecting the future. We are looking for a visionary Lead AI Architect to guide our strategic roadmap, ensuring our AI systems are scalable, secure, and revolutionary by the year 2026.
In this high-impact role, you will bridge the gap between theoretical AI research and production-grade engineering. You will lead a team of elite engineers in deploying next-generation machine learning models that solve complex, real-world problems.
Why Join Us?
- Shape the Future: Directly influence the architecture that powers our vision for 2026.
- Top-Tier Compensation: Competitive salary and equity package.
- Flexible Environment: Remote-first culture with a San Francisco hub.
Ready to build the future? Apply today.
Responsibilities
- Strategic Roadmap: Define and execute the architectural vision for AI systems leading up to the 2026 milestone.
- System Design: Design scalable, high-performance distributed systems and machine learning pipelines.
- Technical Leadership: Mentor senior and junior engineers, conducting code reviews and architectural reviews.
- Research Integration: Translate cutting-edge research into production-ready code and scalable infrastructure.
- Collaboration: Partner with product managers and data scientists to align technical solutions with business goals.
- Performance Optimization: Continuously monitor system performance and optimize for speed, latency, and cost-efficiency.
Qualifications
- Education: Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 8+ years of software engineering experience with 5+ years in AI/ML architecture.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and distributed systems (Kubernetes, Docker).
- Leadership: Demonstrated experience leading engineering teams and managing cross-functional projects.
- Communication: Exceptional ability to articulate complex technical concepts to non-technical stakeholders.
- Problem Solving: Deep understanding of algorithm design, data structures, and system scalability.