Job Description
Shape the Future of Intelligence. Nebula Horizon Labs is pioneering the next generation of autonomous AI systems. As we look toward the technological landscape of 2026, we are seeking a visionary Principal AI Architect to lead our research and engineering division.
In this role, you will define the architectural blueprint for our upcoming suite of Generative AI agents and Reasoning Models. You won't just be building models; you will be engineering the infrastructure that powers the next evolution of human-machine interaction. If you are obsessed with pushing the boundaries of Large Language Models (LLMs), optimizing inference latency, and ensuring ethical AI deployment, we want to talk to you.
Why Join Us?
- Work on cutting-edge technology predicted to define the 2026 tech ecosystem.
- Competitive compensation package with equity options.
- Top-tier benefits and a remote-first culture focused on deep work.
Ready to architect the impossible? Apply today.
Responsibilities
- Architectural Leadership: Design scalable, fault-tolerant AI infrastructures capable of supporting millions of concurrent inference requests.
- Model Strategy: Define the roadmap for our proprietary LLMs and multi-modal agents, focusing on reasoning capabilities and cost-efficiency.
- System Optimization: Lead initiatives to reduce model latency and optimize memory usage for edge deployment scenarios.
- MLOps Implementation: Oversee the deployment of CI/CD pipelines for machine learning models, ensuring rigorous testing and validation.
- Cross-Functional Collaboration: Partner with product managers and data scientists to translate complex business requirements into technical AI solutions.
- Technical Mentorship: Mentor a team of senior engineers and researchers, fostering a culture of innovation and continuous learning.
- Ethical AI Governance: Establish guidelines and best practices for AI safety, fairness, and transparency in our output.
Qualifications
- Education: Master’s degree in Computer Science, Artificial Intelligence, or a related field; PhD preferred.
- Experience: 8+ years of experience in machine learning engineering, with at least 3 years in a leadership or architect role.
- Technical Stack: Deep expertise in Python, PyTorch, TensorFlow, and modern MLOps tools (Kubeflow, MLflow).
- Model Mastery: Proven track record of working with Large Language Models (GPT, Llama, Claude) and fine-tuning strategies.
- System Design: Strong understanding of distributed systems, cloud architecture (AWS/GCP/Azure), and high-performance computing.
- Problem Solving: Ability to tackle complex algorithmic challenges and optimize deep neural networks for production environments.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders.