Job Description
Are you ready to define the future of intelligent systems? Nebula Core Systems is launching the '2026 Initiative'—a groundbreaking research program aimed at solving complex global challenges through advanced artificial intelligence.
We are seeking a visionary Senior AI Architect to lead the architectural design of our next-generation neural networks and generative AI models. You will work at the intersection of theoretical research and scalable engineering, pushing the boundaries of what's possible in 2026 and beyond.
Why Join Us?
- Work on cutting-edge technology that will define the next decade.
- Competitive compensation package including equity.
- Remote-first culture with hubs in San Francisco and Seattle.
Role Overview: You will be responsible for the end-to-end architecture of our AI products, ensuring they are scalable, robust, and future-proof. You will guide the engineering team in adopting best practices and deploying state-of-the-art models.
Responsibilities
- Lead Architectural Design: Spearhead the design and implementation of scalable, high-performance AI infrastructure for the 2026 Initiative.
- Research & Development: Collaborate with PhD researchers to translate theoretical models into production-ready software.
- Model Optimization: Engineer solutions to optimize model latency, memory usage, and inference speed.
- Team Leadership: Mentor a team of junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Cross-Functional Collaboration: Partner with product managers and stakeholders to align AI capabilities with business goals.
- Technical Strategy: Define the technical roadmap and best practices for the AI engineering team.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 5+ years of professional experience in machine learning, deep learning, or AI architecture.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and Hugging Face libraries.
- Domain Knowledge: Strong background in Natural Language Processing (NLP), Computer Vision, or Reinforcement Learning.
- System Design: Experience designing distributed systems and cloud-native AI workloads (AWS/GCP).
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.