Job Description
Are you ready to architect the intelligence systems that will define the 2026 era? Nebula Innovations is seeking a visionary Senior AI Architect to lead our cutting-edge research division focused on Artificial General Intelligence (AGI) and autonomous agents.
In this pivotal role, you will bridge the gap between theoretical machine learning breakthroughs and scalable production infrastructure. You will define the architectural standards for our next-generation neural networks, ensuring they are robust, ethical, and capable of adapting to the evolving digital landscape of 2026.
Why join Nebula Innovations?
- Work at the forefront of the AI revolution with a team of world-class engineers.
- Competitive equity package and a culture that prioritizes deep work and innovation.
- Flexible remote-first policy with quarterly global team retreats.
We are looking for a builder who isn't afraid to push the boundaries of what is possible with Large Language Models (LLMs) and multimodal AI systems.
Responsibilities
- Architect Next-Gen AI Systems: Design and implement scalable, fault-tolerant architectures for large-scale Generative AI models and autonomous agents.
- Pipeline Optimization: Oversee the end-to-end ML pipeline, from data ingestion and feature engineering to model training, fine-tuning, and deployment.
- Ethical AI Implementation: Establish and enforce guidelines for AI safety, fairness, and transparency to mitigate bias and ensure responsible deployment.
- Cross-Functional Leadership: Collaborate closely with product managers, data scientists, and software engineers to translate business requirements into technical solutions.
- R&D Innovation: Stay ahead of the curve on emerging AI trends, researching and prototyping novel architectures that provide a competitive edge.
- Code Quality & Mentorship: Mentor junior engineers and conduct technical reviews to maintain high standards of code quality and engineering best practices.
Qualifications
- Education: Master’s degree or PhD in Computer Science, Mathematics, or a related field (PhD preferred).
- Experience: 7+ years of experience in software engineering, with at least 4 years specifically focused on Machine Learning and Deep Learning.
- Technical Stack: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with cloud platforms (AWS/GCP/Azure) and containerization (Docker/Kubernetes).
- Model Expertise: Deep understanding of Transformer architectures, Reinforcement Learning from Human Feedback (RLHF), and RAG (Retrieval-Augmented Generation) pipelines.
- Problem Solving: Demonstrated ability to solve complex, unstructured problems and optimize system performance under high load.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.