Job Description
Welcome to the future of technology. Nebula Horizon is at the forefront of defining the technological landscape of 2026 and beyond. We are looking for a visionary Senior Architect: AI & Autonomous Systems to lead our research and engineering division.
In this pivotal role, you will design the core infrastructure for autonomous decision-making systems and next-generation neural interfaces. You won't just be coding; you will be architecting the future of human-machine interaction. Join us in building the scalable, ethical, and robust frameworks that will power the next decade of innovation.
Why Join Us?
- Work with a world-class team of futurists and engineers.
- Shape the roadmap for autonomous AI agents.
- Competitive compensation package and equity options.
- Flexible remote-first culture with a hub in San Francisco.
Responsibilities
- Architect Core Systems: Design and implement scalable, high-performance AI architectures for autonomous decision-making systems.
- Roadmap Leadership: Define the technical roadmap for 2026, aligning AI capabilities with business objectives and futuristic trends.
- Model Optimization: Oversee the training and fine-tuning of large language models and neural networks for real-time processing.
- Team Mentorship: Lead a cross-functional team of data scientists, ML engineers, and researchers to ensure technical excellence.
- Ethical AI Governance: Establish and enforce best practices for AI ethics, safety, and bias mitigation in all deployed systems.
- Prototyping: Spearhead the development of proof-of-concept prototypes for emerging technologies like neuromorphic computing.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
- Experience: 8+ years of experience in software engineering, with at least 4 years in AI/ML architecture and leadership.
- Technical Skills: Proficiency in Python, C++, and TensorFlow/PyTorch. Deep understanding of distributed systems and cloud infrastructure (AWS/Azure/GCP).
- Domain Knowledge: Strong background in Reinforcement Learning, Natural Language Processing (NLP), or Computer Vision.
- Leadership: Proven track record of leading high-performing engineering teams and managing complex technical projects.
- Problem Solving: Exceptional ability to translate abstract business problems into robust technical solutions.