Job Description
Are you ready to architect the world of 2026? At Chronos Future Systems, we are not just predicting the future; we are building the foundational technology that will define the next decade. We are seeking a visionary Senior AI Architect to lead our core infrastructure initiatives designed for the autonomous era.
As a key member of our elite engineering team, you will design scalable, fault-tolerant machine learning models that power our smart city and autonomous logistics platforms. You will bridge the gap between theoretical AI research and production-grade systems, ensuring our platforms are ready for the demands of the year 2026 and beyond.
Why join the 2026 Vision Team?
- Work on cutting-edge AI infrastructure.
- Competitive equity and benefits package.
- Shape the roadmap for the next generation of technology.
Responsibilities
- Lead System Architecture: Design and implement scalable, distributed machine learning pipelines capable of handling petabyte-scale data streams in real-time.
- Model Optimization: Engineer high-performance models for Natural Language Processing (NLP) and Computer Vision, optimizing for latency and inference speed.
- Future-Proofing: Architect systems with quantum-ready protocols and edge computing integration to ensure readiness for emerging technologies.
- Technical Leadership: Mentor junior engineers and define coding standards for AI projects within the organization.
- Collaboration: Partner with cross-functional teams (Product, Security, and Data Science) to translate business requirements into technical solutions.
- Research Integration: Evaluate and integrate emerging research papers into practical production applications.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Experience: 7+ years of experience in software engineering, with at least 3 years focused on AI/ML architecture.
- Core Skills: Proficiency in Python, TensorFlow, PyTorch, and experience with large language model (LLM) fine-tuning.
- System Design: Strong understanding of distributed systems, microservices, and cloud architecture (AWS, GCP, or Azure).
- Problem Solving: Demonstrated ability to solve complex engineering problems with innovative solutions.
- Communication: Excellent verbal and written communication skills for technical and non-technical stakeholders.