Job Description
We are pioneering the next generation of artificial intelligence, and we are looking for a visionary Senior AI Architect to define our 2026 roadmap. In this role, you will not just implement existing models but architect the foundational systems that will define the future of human-computer interaction. Join us in building the intelligent infrastructure of tomorrow.
Why Join Nexus Future Systems?
- Work on cutting-edge Agentic AI and Large Language Models.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in the heart of San Francisco.
- Access to state-of-the-art compute resources and research libraries.
Responsibilities
- Lead the architectural design of scalable, high-performance AI models tailored for the 2026 technology landscape.
- Oversee the full machine learning lifecycle, from data ingestion and feature engineering to model deployment and monitoring.
- Collaborate with cross-functional teams (Product, Engineering, Design) to translate complex business requirements into robust AI solutions.
- Implement robust MLOps pipelines to ensure model reliability, security, and continuous improvement.
- Stay ahead of industry trends to integrate emerging technologies (e.g., quantum computing interfaces, advanced neural architectures) into our core stack.
- Conduct code reviews and mentor junior engineers, fostering a culture of technical excellence and innovation.
- Drive ethical AI initiatives, ensuring fairness, transparency, and safety in all AI deployments.
Qualifications
- Master’s or Ph.D. in Computer Science, Machine Learning, or a related quantitative field (or equivalent professional experience).
- Minimum of 5-7 years of experience in designing, training, and deploying large-scale machine learning systems.
- Deep expertise in Python, PyTorch, TensorFlow, or JAX.
- Strong proficiency in cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Proven track record of working with Large Language Models (LLMs) and Generative AI frameworks.
- Experience with vector databases and RAG (Retrieval-Augmented Generation) architectures.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.