Job Description
Welcome to the future of intelligence. Nexus Horizon Labs is pioneering the autonomous neural architectures that will define 2026 and beyond. We are seeking a visionary Senior AI Research Scientist to lead our breakthrough team in developing scalable, multimodal AI systems that learn, reason, and adapt in real-time.
In this role, you won't just be writing code; you will be architecting the cognitive layer of the next generation of digital consciousness. We operate at the intersection of deep learning, cognitive science, and advanced robotics.
Why Join Us?
- Work on projects that shape the ethical and technical foundation of Artificial General Intelligence.
- Competitive compensation package including equity and performance bonuses.
- Access to state-of-the-art compute resources and a collaborative, elite engineering culture.
If you are driven by the challenge of solving unsolved problems and want to be at the vanguard of the AI revolution, we want to hear from you.
Responsibilities
- Architect Development: Design and implement novel deep learning architectures for large-scale language and vision models.
- Research Leadership: Spearhead research initiatives in reinforcement learning and few-shot learning to improve model efficiency.
- Model Optimization: Optimize training pipelines and reduce inference costs for edge deployment.
- Collaboration: Partner with product teams to translate theoretical research into tangible, scalable product features.
- Mentorship: Guide and mentor junior researchers and data scientists within the team.
- Publication: Author high-impact research papers for top-tier conferences (NeurIPS, ICML, ICLR).
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, or a related field with a focus on AI/ML.
- Experience: Minimum of 5+ years of professional experience in research engineering or applied machine learning.
- Technical Skills: Proficiency in Python, PyTorch, and TensorFlow. Deep understanding of transformer models and generative adversarial networks.
- Mathematics: Strong foundation in linear algebra, calculus, and probability theory.
- Problem Solving: Proven track record of solving complex, ambiguous problems in high-velocity environments.