Job Description
Are you ready to shape the technological landscape of 2026? OmniFuture Systems is seeking a visionary Next-Gen AI Architect to lead our cutting-edge research division. In this pivotal role, you will define the architecture for AI systems that will define the future of human-machine interaction. We are not just building software; we are architecting the intelligence infrastructure for the next decade.
Why Join Us?
Work at the forefront of innovation in the heart of San Francisco. You will have the autonomy to experiment with the latest breakthroughs in Generative AI, Reinforcement Learning, and Neural Symbolic AI. We offer a competitive compensation package, equity options, and a culture that prioritizes intellectual curiosity and technical excellence.
The Role:
As an AI Architect, you will bridge the gap between theoretical research and scalable production engineering. You will be responsible for the end-to-life cycle of our AI products, ensuring they are robust, ethical, and ready for the demands of 2026 and beyond.
Responsibilities
- Architect and implement scalable, next-generation AI/ML infrastructure designed for the 2026 technological landscape.
- Lead the research and deployment of Large Language Models (LLMs) and generative AI solutions.
- Optimize deep learning models for high-performance inference on edge devices and cloud environments.
- Establish and enforce best practices for AI ethics, data privacy, and responsible AI governance.
- Collaborate cross-functionally with product and engineering teams to define the 2026 roadmap.
- Mentor senior engineers and foster a culture of innovation and technical excellence.
Qualifications
- Master’s or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- 7+ years of professional experience in designing and deploying machine learning systems.
- Expert proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of working with NLP, Computer Vision, or Reinforcement Learning.
- Experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Strong understanding of distributed systems and system design principles.