Job Description
Join the Architects of Tomorrow
Nexus Future Labs is at the forefront of defining the technological landscape for the year 2026 and beyond. We are seeking a visionary Senior AI & Future Tech Architect to lead our R&D initiatives in Generative AI, Advanced Robotics, and Quantum-ready infrastructure. If you are passionate about building scalable, ethical, and revolutionary systems that will define the future, we want to hear from you.
In this role, you will bridge the gap between theoretical innovation and practical application, ensuring our platforms are not just ready for 2026, but are the standard-setters for the decade.
Why Join Us?
- Work on cutting-edge projects that shape the global technological trajectory.
- Competitive compensation package with equity options.
- Flexible remote-first policy with a hub in the heart of San Francisco.
Responsibilities
- Architect and design scalable AI infrastructure capable of processing petabytes of data for 2026 enterprise standards.
- Lead the research and implementation of Generative AI models, focusing on safety, bias reduction, and efficiency.
- Collaborate with quantum computing researchers to develop hybrid algorithms for future-proof applications.
- Define technical roadmaps for the '2026 Vision' product suite, ensuring alignment with business goals.
- Mentor junior engineers and data scientists, fostering a culture of innovation and continuous learning.
- Conduct rigorous code reviews and ensure architectural integrity across all development teams.
Qualifications
- Master’s degree in Computer Science, Artificial Intelligence, or a related field (PhD preferred).
- 10+ years of experience in software architecture, with at least 5 years in AI/ML engineering.
- Deep expertise in Python, TensorFlow, PyTorch, and modern Cloud Architectures (AWS/Azure/GCP).
- Proven track record of deploying large-scale machine learning models into production environments.
- Strong understanding of ethical AI principles and data governance frameworks.
- Experience with high-performance computing clusters and edge computing architectures.