Job Description
Are you ready to define the trajectory of Artificial Intelligence? 2026 is not just a company; we are the architects of the future, building the autonomous systems that will define the next decade. We are seeking a visionary Senior AI Research Scientist to join our elite R&D team in San Francisco.
In this role, you will push the boundaries of what is possible with Large Language Models (LLMs), Computer Vision, and Reinforcement Learning. You won't just be writing code; you will be solving complex problems that impact millions of users globally. If you are passionate about ethical AI, deep learning, and building systems that learn to think, we want to hear from you.
Why Join 2026?
- Work with state-of-the-art hardware and cloud infrastructure.
- Competitive equity package and top-tier benefits.
- A culture that values radical transparency and continuous learning.
Responsibilities
- Lead the research and development of novel deep learning architectures and algorithms for next-gen AI applications.
- Design and implement scalable machine learning pipelines that handle terabytes of data efficiently.
- Collaborate with cross-functional teams including product managers, engineers, and designers to translate research into production-ready products.
- Publish high-impact research papers at top-tier conferences (NeurIPS, ICML, ICLR) and contribute to the open-source community.
- Mentor junior researchers and data scientists, fostering a culture of innovation and technical excellence.
- Stay abreast of the latest advancements in AI and NLP to ensure our technology remains ahead of the curve.
Qualifications
- PhD or Master’s degree in Computer Science, Mathematics, Statistics, or a related field.
- 5+ years of professional experience in Machine Learning or Artificial Intelligence, preferably in a research or tech-heavy industry.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Proven track record of publishing research in top-tier venues or shipping complex ML products at scale.
- Deep understanding of Transformer models, LLMs, and fine-tuning techniques (PEFT, LoRA).
- Experience with MLOps tools such as MLflow, Kubernetes, or AWS SageMaker.