Job Description
Are you ready to define the next era of technology? Chronos AI Labs is building the infrastructure for the Project 2026 initiative—a groundbreaking leap into general artificial intelligence. We are seeking a visionary Lead AI Architect to design the neural architectures that will power the world's most advanced cognitive systems.
In this role, you will bridge the gap between theoretical research and practical deployment, ensuring our systems are not only intelligent but scalable, ethical, and future-proof. You will work alongside quantum computing experts and cognitive scientists to pioneer the next generation of AI models.
Why join Project 2026?
- Shape the foundational code of future intelligence.
- Work with state-of-the-art hardware and quantum processors.
- Competitive equity package and top-tier benefits.
If you are passionate about the future and possess the technical prowess to build it, we want to meet you.
Responsibilities
- Design and implement scalable, fault-tolerant neural network architectures for AGI development.
- Lead the research and development of proprietary algorithms, focusing on efficiency and cognitive depth.
- Collaborate with cross-functional teams to integrate AI models into real-world applications and robotics.
- Establish best practices for data governance, model transparency, and ethical AI usage.
- Oversee the technical mentorship of junior engineers and data scientists within the project team.
- Optimize existing models for edge computing environments and high-performance clusters.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, or a related field (or equivalent practical experience).
- 10+ years of professional experience in AI/ML engineering, with at least 5 years in a leadership or architect role.
- Expert proficiency in Python, C++, and deep learning frameworks such as PyTorch or TensorFlow.
- Deep understanding of Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- Experience working with quantum computing libraries or hybrid quantum-classical algorithms.
- Strong grasp of software engineering principles, including CI/CD, version control, and cloud infrastructure.