Job Description
Are you ready to define the technological landscape of 2026? Neural Horizon Labs is seeking visionary AI Research Scientists to pioneer breakthroughs in generative intelligence and quantum-enhanced machine learning. We are building the infrastructure for the future, and we need a team of elite engineers and researchers to lead the charge.
In this role, you will not just adapt to the future; you will architect it. Join us in San Francisco to work on cutting-edge projects that will set the standard for Artificial General Intelligence (AGI) in the coming years.
Why Join Us?
- Work on the 2026 Horizon Initiative, a top-secret R&D project focused on next-gen neural networks.
- Competitive compensation and equity packages for top-tier talent.
- Access to state-of-the-art hardware and quantum computing resources.
- Flexible remote and hybrid work options within the US.
Responsibilities
- Lead Architecture Design: Spearhead the development of novel neural architectures optimized for the computing paradigms of 2026, including neuromorphic computing and edge AI integration.
- Research & Development: Conduct high-impact research in Natural Language Processing (NLP), Computer Vision, and Reinforcement Learning to achieve state-of-the-art performance metrics.
- Model Optimization: Refine and scale large-scale models to ensure efficiency, low latency, and high throughput in production environments.
- Collaboration: Partner with cross-functional teams of software engineers, data scientists, and product managers to translate theoretical research into practical applications.
- Mentorship: Guide junior researchers and contribute to the technical culture by conducting code reviews and technical workshops.
- Publishing: Author and present high-impact research papers at leading AI conferences (NeurIPS, ICML, ICLR).
Qualifications
- Education: Ph.D. or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
- Experience: 5+ years of professional experience in AI/ML research or a related engineering role, with a strong focus on deep learning frameworks.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, or JAX. Experience with distributed training and high-performance computing clusters.
- Algorithmic Expertise: Deep understanding of statistical modeling, optimization algorithms, and neural network theory.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to diverse audiences.
- Adaptability: Demonstrated ability to thrive in fast-paced, dynamic environments and adapt to rapidly evolving technologies.