Job Description
We are seeking a visionary Predictive AI Architect to define the technological roadmap for the year 2026. At Chronos Analytics, we don't just predict trends; we engineer the future. You will be at the forefront of developing scalable machine learning models and strategic frameworks designed to solve complex problems two years into the future.
In this high-impact role, you will bridge the gap between theoretical future tech and current engineering realities. You will lead a team of data scientists and engineers in building robust architectures that ensure our clients stay ahead of the curve. If you are passionate about the convergence of artificial intelligence, strategic foresight, and high-performance computing, this is your opportunity to leave a lasting legacy.
Responsibilities
- Architect and lead the development of predictive AI models specifically tailored for the 2026 market landscape.
- Define and execute the long-term technology roadmap, aligning technical capabilities with business goals for the coming years.
- Design scalable data pipelines that can handle high-velocity data streams required for future forecasting.
- Collaborate with cross-functional teams to integrate AI solutions into existing enterprise ecosystems.
- Mentor junior developers and data scientists, fostering a culture of innovation and continuous learning.
- Conduct rigorous testing and validation of future-proof algorithms to ensure reliability.
Qualifications
- Minimum of 5+ years of experience in AI architecture, machine learning engineering, or data science.
- Deep expertise in programming languages such as Python, C++, and frameworks like TensorFlow or PyTorch.
- Strong understanding of big data technologies (Spark, Hadoop) and cloud infrastructure (AWS, Azure, GCP).
- Demonstrated ability to translate complex strategic visions into actionable technical roadmaps.
- Proven track record of leading teams and managing large-scale projects.
- Advanced degree in Computer Science, Data Science, or a related technical field is preferred.