Job Description
We are not just building software; we are architecting the reality of 2026. At Chronos Technologies, we are pioneering the next generation of artificial intelligence, bridging the gap between current capabilities and the transformative technologies of the future. We are seeking a visionary Senior Futurist AI Architect to lead our R&D division and define the roadmap for autonomous systems, quantum-assisted machine learning, and ethical AI governance.
If you are driven by the challenge of solving unsolved problems and possess an instinct for the bleeding edge of technology, we want to hear from you. Join us in shaping the landscape of the future.
Responsibilities
- Architect Future-Proof Systems: Design scalable neural network architectures capable of handling the data complexity expected in 2026 and beyond.
- Quantum Integration: Collaborate with quantum computing researchers to integrate hybrid classical-quantum algorithms into production pipelines.
- Strategic Roadmapping: Lead the '2026 Readiness' initiative, identifying emerging trends in Generative AI and deploying pre-emptive solutions.
- High-Performance Computing: Optimize deep learning models for latency and throughput on distributed cloud infrastructures.
- AI Governance: Establish frameworks for ethical AI, bias mitigation, and data privacy compliance in autonomous agent systems.
- Technical Mentorship: Cultivate a culture of innovation by mentoring senior engineers and fostering a deep understanding of AI ethics.
Qualifications
- Education: Master’s or PhD in Computer Science, Computational Physics, or a related field.
- Experience: 8+ years of professional experience in AI/ML engineering with a focus on large language models (LLMs) and transformers.
- Technical Stack: Expert proficiency in Python, PyTorch, TensorFlow, and CUDA programming.
- Innovation: Demonstrated history of publishing patents or leading breakthrough projects in emerging tech fields.
- Cloud Mastery: Extensive experience with AWS, Google Cloud Platform, or Azure, specifically within AI services.
- Problem Solving: Ability to translate abstract theoretical concepts into robust, deployable software solutions.