Job Description
We are not just building for today; we are architecting the infrastructure for the year 2026. Nexus Future Systems is seeking a visionary Senior AI Architect to lead the development of next-generation generative AI and autonomous systems. In this pivotal role, you will define the technical roadmap that bridges the gap between current machine learning capabilities and the advanced, autonomous landscapes of 2026.
As a key member of our elite R&D division, you will have the freedom to experiment, innovate, and implement cutting-edge technologies that will redefine industry standards. If you are passionate about the future of technology and possess a deep understanding of scalable AI architectures, we want to hear from you.
Why Join Us?
- Work on ground-breaking projects that shape the 2026 technological landscape.
- Competitive compensation package with equity opportunities.
- Flexible remote-first policy with premium co-working spaces in SF.
Responsibilities
- Architect Future-Proof Systems: Design and implement scalable AI infrastructure capable of handling the demands of the 2026 era, focusing on generative models and large language models.
- R&D Leadership: Lead research initiatives to explore emerging technologies, including Quantum AI integration and edge computing optimization.
- Model Optimization: Oversee the fine-tuning and deployment of proprietary models to ensure maximum performance, accuracy, and latency reduction.
- Cross-Functional Collaboration: Partner with product managers, data scientists, and engineers to translate business requirements into robust technical solutions.
- Security & Compliance: Implement rigorous security protocols to ensure data privacy and compliance with evolving global regulations.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, or a related field; PhD preferred.
- Experience: Minimum of 7+ years of experience in software engineering and machine learning architecture.
- Technical Skills: Deep expertise in Python, TensorFlow, PyTorch, and distributed systems. Experience with MLOps and cloud platforms (AWS/GCP/Azure) is mandatory.
- Innovation Mindset: Proven track record of implementing novel solutions in complex environments. Must demonstrate a clear vision for the future of AI.
- Communication: Excellent ability to articulate complex technical concepts to non-technical stakeholders and leadership teams.