Job Description
We are pioneering the next generation of Artificial General Intelligence (AGI) and are looking for a visionary Senior AI Research Engineer to join our '2026 Vision' division. At Nexus Horizon Labs, we don't just predict the future of technology; we build it. In this role, you will be at the forefront of developing scalable neural architectures designed to transform industries by 2026 and beyond.
Our mission is to bridge the gap between theoretical breakthroughs and practical, transformative applications. You will work with a world-class team of cognitive scientists, ethicists, and software engineers to solve the hardest problems in machine learning, including reasoning, memory, and autonomy.
Why Join Us?
- Work on cutting-edge research that defines the AI landscape of 2026.
- Competitive compensation and equity packages.
- Flexible remote-first policy with access to state-of-the-art computing infrastructure.
Ready to shape the future? Apply today.
Responsibilities
- Design and implement novel deep learning architectures tailored for the 2026 AI roadmap, focusing on reasoning and autonomy.
- Lead end-to-end research initiatives from hypothesis generation to large-scale model deployment.
- Collaborate with cross-functional teams to integrate research findings into production-grade software systems.
- Optimize model inference performance and reduce computational costs for real-time applications.
- Mentor junior researchers and contribute to the academic and technical community.
- Stay ahead of the curve by analyzing global tech trends and identifying strategic research opportunities.
Qualifications
- PhD or Master's degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- 5+ years of professional experience in machine learning research or a related engineering role.
- Strong proficiency in Python, PyTorch, or TensorFlow, with experience in C++ for performance optimization.
- Proven track record of publishing in top-tier conferences (NeurIPS, ICML, ICLR) or delivering impactful open-source contributions.
- Deep understanding of large language models, transformers, or reinforcement learning.
- Excellent communication skills and the ability to articulate complex technical concepts to diverse stakeholders.