Job Description
Welcome to the future of intelligence. Nebula Dynamics is seeking a visionary Senior AI Architect to lead our core research into Generative AI and Autonomous Agents for the 2026 era. If you are passionate about pushing the boundaries of what is possible with Large Language Models (LLMs) and ethical artificial intelligence, this is your chance to shape the roadmap of tomorrow.
In this pivotal role, you will design scalable AI systems, mentor a team of elite engineers, and bridge the gap between theoretical research and production-grade deployment. We offer a competitive compensation package, equity options, and a culture that prioritizes innovation and intellectual curiosity.
Why Join Us?
- Future-First Technology: Work on the bleeding edge of AI development, preparing infrastructure for the post-AGI landscape.
- Top-Tier Compensation: Competitive base salary ($180k - $260k) plus performance bonuses.
- Unlimited PTO & Remote Flexibility: We trust our experts to manage their time effectively.
- State-of-the-Art Stack: Access to the latest GPUs and cloud infrastructure (AWS/GCP).
Responsibilities
- Architect and implement next-generation neural network architectures for high-performance inference.
- Lead the end-to-end lifecycle of AI model development, from data ingestion to fine-tuning and deployment.
- Define the technical roadmap for Nebula Dynamics' AI products in alignment with 2026 strategic goals.
- Collaborate with cross-functional teams (Product, Security, Engineering) to integrate AI solutions into enterprise workflows.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Evaluate emerging AI frameworks (e.g., PyTorch, TensorFlow, JAX) and open-source innovations.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Mathematics, or a related field (PhD preferred).
- 5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
- Proficiency in Python, C++, and modern machine learning libraries.
- Strong understanding of Transformer models, NLP, and multimodal architectures.
- Experience with cloud infrastructure (AWS, Azure, or Google Cloud) and containerization (Docker/Kubernetes).
- Proven track record of deploying scalable AI systems in production environments.
- Exceptional problem-solving skills and the ability to thrive in a fast-paced, ambiguous environment.