Job Description
Are you ready to define the future of Artificial Intelligence? Nexus Horizon is pioneering the 2026 AI Vision, a groundbreaking initiative to bridge the gap between Generative AI and Artificial General Intelligence (AGI). We are looking for a visionary Research Scientist to lead our architecture team and push the boundaries of what is possible in machine learning.
In this role, you will not just build models; you will architect the cognitive frameworks of tomorrow. You will collaborate with a world-class team of ethicists, engineers, and futurists to ensure our AI systems are safe, scalable, and revolutionary. Join us in shaping the digital landscape of 2026 and beyond.
Why Nexus Horizon?
- Work on cutting-edge AGI research with a competitive compensation package.
- Flexible remote-first culture with a hub in the vibrant tech scene of Austin, TX.
- Equity package and annual innovation grants.
- Focus on ethical AI development and long-term impact.
Responsibilities
- Architect and optimize next-generation neural networks capable of complex reasoning and autonomous learning.
- Lead the research and implementation of large language models (LLMs) specifically tuned for 2026 enterprise applications.
- Define the technical roadmap for the company's AI evolution, aligning with the 2026 strategic vision.
- Conduct rigorous testing and validation of AI models to ensure safety, bias mitigation, and high performance.
- Mentor junior researchers and data scientists, fostering a culture of continuous innovation.
- Publish high-impact research papers and present at global tech conferences.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, Cognitive Science, or a related technical field.
- Extensive experience in Python, PyTorch, TensorFlow, or JAX.
- Deep understanding of transformer architectures, reinforcement learning, and natural language processing.
- Proven track record of publishing in top-tier AI conferences (NeurIPS, ICML, ACL) or comparable industry research.
- Strong background in ethical AI practices and responsible machine learning governance.
- Ability to translate complex technical concepts into scalable engineering solutions.