Job Description
At 2026, we are not merely predicting the future; we are engineering it. We are a forward-thinking technology collective dedicated to solving humanity's most complex challenges through advanced artificial intelligence. Our mission is to build the infrastructure that powers the next decade of digital evolution.
We are seeking a visionary Senior AI Research Scientist to join our elite team in San Francisco. In this role, you will be at the forefront of generative modeling, pushing the boundaries of what is possible with Large Language Models (LLMs) and multimodal AI systems. You will work in a highly collaborative environment, bridging the gap between theoretical research and real-world application.
If you are passionate about the intersection of data, code, and creativity, and you want to leave a legacy in the tech landscape, we want to hear from you.
Responsibilities
- Lead Research Initiatives: Spearhead the development and optimization of state-of-the-art deep learning models, focusing on natural language processing and generative AI.
- Model Architecture: Design novel neural network architectures and algorithms to improve model performance, efficiency, and interpretability.
- Collaboration: Partner with cross-functional teams of engineers, product managers, and designers to translate research findings into scalable products.
- Publication: Author high-impact research papers and present findings at leading industry conferences and peer-reviewed journals.
- Data Strategy: Curate and manage large-scale datasets, ensuring data quality, ethical use, and bias mitigation.
- Mentorship: Mentor junior researchers and data scientists, fostering a culture of continuous learning and innovation.
Qualifications
- Education: PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related quantitative field.
- Experience: 5+ years of experience in research and development within the AI/ML space.
- Technical Skills: Proficiency in Python, PyTorch, or TensorFlow; deep understanding of transformer models and attention mechanisms.
- Programming: Strong coding skills with the ability to write clean, maintainable, and high-performance code.
- Communication: Excellent written and verbal communication skills, with the ability to explain complex technical concepts to diverse audiences.
- Problem Solving: Proven track record of solving ambiguous problems and navigating the complexities of research and development.