Job Description
Shape the Future of Intelligence. Chronos Systems is pioneering the next era of technological evolution. We are seeking a visionary Lead Neural Architect to join our 2026 Strategic Initiative. If you are obsessed with the potential of Generative AI, Quantum Computing, and Synthetic Cognition, this is your opportunity to build the systems that will define the future.
In this role, you will move beyond standard software engineering to design the cognitive layer of tomorrow. You will bridge the gap between theoretical AI research and production-grade infrastructure, creating scalable neural frameworks that push the boundaries of performance and efficiency.
Why This Role is Unique:
- Future-Proofing: Work on bleeding-edge projects involving Neural Interfaces and Quantum Integration.
- High-Impact Leadership: Architect the core infrastructure that will power our ecosystem for the next decade.
- Elite Environment: Collaborate with world-class researchers and engineers in a state-of-the-art facility.
Responsibilities
- Architect and deploy scalable, high-performance neural network models optimized for 2026 workloads.
- Lead the integration of quantum computing principles into traditional machine learning pipelines.
- Collaborate with cross-functional teams to define the technical roadmap for our upcoming synthetic intelligence products.
- Optimize existing AI models for extreme latency reduction and energy efficiency.
- Mentor a team of senior engineers and data scientists, fostering a culture of innovation.
- Conduct rigorous architectural reviews and ensure code integrity across all projects.
- Stay ahead of industry trends in Generative AI and Large Language Models (LLMs).
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Minimum of 8 years of experience in machine learning engineering, with at least 3 years in a leadership role.
- Deep expertise in Python, TensorFlow, PyTorch, and Hugging Face libraries.
- Experience with distributed systems and high-performance computing (HPC) environments.
- Strong understanding of Deep Reinforcement Learning and Transformer architectures.
- Proven track record of shipping complex AI products to production environments.
- Excellent communication skills and the ability to translate complex technical concepts to stakeholders.