Job Description
Are you ready to define the technological landscape of 2026? Chronos Systems Inc. is seeking a visionary Generative AI Architect to lead the next evolution of intelligent systems. As we prepare for the AI revolution of the coming years, we need a forward-thinking engineer who doesn't just use existing tools but builds the frameworks of tomorrow.
In this pivotal role, you will spearhead the development of proprietary generative models, pushing the boundaries of Large Language Models (LLMs) and multimodal systems. You will work in a high-performance environment with top-tier researchers and engineers, directly influencing the strategic roadmap for our enterprise solutions.
Why Join Us?
- Shape the future of AI in a role designed for 2026 and beyond.
- Competitive compensation package with equity options.
- Access to cutting-edge hardware and cloud infrastructure.
- Flexible remote-first culture with collaborative hubs in SF.
Responsibilities
- Design and implement scalable architecture for large-scale generative models, ensuring high performance and low latency.
- Lead the research and development of novel algorithms to improve model accuracy, creativity, and efficiency.
- Collaborate with cross-functional teams to integrate AI models into production environments using MLOps best practices.
- Define technical standards and mentor junior engineers to foster a culture of innovation.
- Stay ahead of industry trends, specifically focusing on the trajectory of AI capabilities by 2026.
- Conduct rigorous testing and validation of model outputs to ensure safety, bias mitigation, and regulatory compliance.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- 5+ years of professional experience in machine learning engineering, with 3+ years specifically in NLP or Generative AI.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Deep understanding of transformer architectures, attention mechanisms, and deep learning principles.
- Experience with deploying models on cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.