Job Description
We are pioneering the next generation of Artificial General Intelligence with our flagship project, Project 2026. We are seeking elite technical talent to help us architect the algorithms that will power the future of human-machine collaboration. If you are passionate about pushing the boundaries of Large Language Models (LLMs) and Reinforcement Learning, we want to hear from you.
In this role, you will work directly with our research scientists and engineers to optimize model architecture, improve inference efficiency, and ensure our models are safe, ethical, and scalable.
Why join us?
- Work on cutting-edge AI research that impacts billions of users.
- Competitive equity package and benefits.
- Flexible remote-first culture with a hub in the heart of San Francisco.
Responsibilities
- Design and implement novel model architectures to enhance the reasoning capabilities of the 2026 system.
- Conduct rigorous empirical research to fine-tune pre-trained models for specific domain applications.
- Optimize model inference speed and memory usage to support real-time deployment at scale.
- Collaborate with the safety team to align model outputs with ethical guidelines and safety standards.
- Publish research findings in top-tier conferences (NeurIPS, ICML, ICLR) and contribute to open-source communities.
- Debug complex distributed training issues and ensure high availability of training infrastructure.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related technical field.
- 5+ years of experience in Machine Learning, Deep Learning, or Natural Language Processing.
- Strong proficiency in Python, PyTorch, or TensorFlow.
- Extensive experience working with transformer models (BERT, GPT, T5) and fine-tuning techniques.
- Deep understanding of optimization algorithms, distributed computing, and GPU acceleration.
- Excellent problem-solving skills and the ability to work in a fast-paced, agile environment.