Job Description
OmniFuture Systems is pioneering the Project 2026 initiative, a groundbreaking endeavor to redefine the boundaries of artificial general intelligence. We are seeking a visionary Lead AI Architect to spearhead the development of our next-generation neural frameworks. You will be at the forefront of integrating cutting-edge generative models with robust, scalable infrastructure, ensuring our solutions are not only intelligent but also resilient and future-proof.
In this role, you will bridge the gap between theoretical research and production-grade engineering. You will lead a high-performance team of machine learning engineers and data scientists, setting architectural standards that will guide our technology roadmap for the next decade. If you are passionate about the future of AI and want to build systems that think, learn, and adapt at a human-like level, we want to hear from you.
Why Join Us?
- Work on the bleeding edge of AI development for a Fortune 500 client.
- Competitive compensation package including equity options.
- Flexible remote-first policy with a hub in San Francisco.
- Access to state-of-the-art computing resources and research papers.
Responsibilities
- Design and architect scalable, fault-tolerant AI systems capable of processing exascale data streams in real-time.
- Lead the technical vision for Project 2026, ensuring alignment with long-term strategic goals.
- Oversee the deployment and optimization of Large Language Models (LLMs) and multi-modal systems.
- Establish coding standards, review code, and mentor junior engineers to foster a culture of excellence.
- Collaborate with product managers and data scientists to translate complex requirements into technical specifications.
- Conduct performance tuning and security audits on AI infrastructure to ensure reliability and compliance.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Artificial Intelligence, or a related technical field.
- 10+ years of experience in software engineering, with at least 5 years in a lead architecture role.
- Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tools (Kubernetes, Docker, MLflow).
- Proven track record of deploying scalable machine learning models to production environments.
- Strong understanding of distributed systems, cloud architecture (AWS/GCP), and high-availability systems.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.