Job Description
We are seeking a visionary Next-Gen AI Architect to lead our 2026 strategic roadmap. At Chronos Dynamics, we don't just predict the future; we engineer it. You will be responsible for architecting the neural infrastructure that powers the next generation of intelligent systems, pushing the boundaries of what is possible in generative AI and autonomous agents.
Why This Role?
This is a high-impact opportunity to define the technical landscape for the year 2026. You will work directly with C-level leadership to build scalable, future-proof AI solutions that solve complex global problems.
Core Competencies:
- Architecting robust large-scale language models (LLMs) and multimodal systems.
- Designing real-time inference pipelines capable of handling enterprise-scale demand.
- Implementing advanced MLOps strategies for continuous model training and deployment.
- Ensuring ethical AI standards and data privacy compliance.
Responsibilities
- System Architecture: Design end-to-end AI architectures for 2026 applications, focusing on scalability, latency, and fault tolerance.
- Model Development: Spearhead the research and implementation of cutting-edge generative models using PyTorch and JAX.
- Infrastructure Optimization: Collaborate with DevOps teams to deploy models on cloud-native platforms (AWS/GCP) using Kubernetes.
- Innovation Leadership: Conduct proof-of-concept experiments to validate emerging technologies before full-scale deployment.
- Team Mentorship: Guide a team of junior engineers and data scientists in best practices for machine learning engineering.
- Stakeholder Communication: Translate complex technical concepts into actionable insights for non-technical stakeholders.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field.
- Experience: 5+ years of professional experience in Machine Learning Engineering, with at least 2 years leading AI infrastructure projects.
- Technical Stack: Deep proficiency in Python, PyTorch, TensorFlow, and experience with distributed training frameworks.
- Cloud Expertise: Strong experience with cloud providers (AWS/Azure/GCP) and containerization technologies (Docker, Kubernetes).
- Problem Solving: Demonstrated ability to tackle complex system design challenges and optimize large-scale data workflows.
- Soft Skills: Excellent communication skills and a passion for the future of technology.