Job Description
We are seeking a visionary Lead AI Architect to define the technological roadmap for our 2026 products. Nexus Future Labs is pioneering the next generation of autonomous systems and generative intelligence. In this pivotal role, you will bridge the gap between theoretical research and scalable production engineering.
As we approach the 2026 technological singularity, we need a leader who understands not just current deep learning architectures, but the emerging paradigms of quantum-enhanced AI and neuromorphic computing. You will work alongside world-class researchers and engineers to build the infrastructure that powers the future of automation.
Why join us?
- Work on cutting-edge technology that will define the 2026 era.
- Competitive equity package and top-tier benefits.
- Flexible remote-first culture with a hub in the heart of SF.
Responsibilities
- Architect and implement scalable deep learning pipelines capable of processing petabytes of real-time data.
- Lead the integration of quantum computing primitives into classical machine learning workflows.
- Mentor a high-performance team of ML engineers and data scientists, fostering a culture of innovation.
- Define technical standards and best practices for model deployment, MLOps, and ethical AI governance.
- Collaborate with product leadership to translate 2026 roadmaps into technical execution plans.
- Conduct rigorous code reviews and performance optimization to ensure zero-latency inference.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, or a related technical field.
- 10+ years of experience in software engineering and machine learning architecture.
- Expert proficiency in Python, PyTorch, TensorFlow, and CUDA programming.
- Deep understanding of Large Language Models (LLMs), diffusion models, and reinforcement learning.
- Proven track record of leading engineering teams through complex architectural transitions.
- Experience with cloud infrastructure (AWS, GCP) and containerization technologies (Kubernetes, Docker).
- Strong understanding of AI ethics, fairness, and bias mitigation.