Job Description
Are you ready to architect the future? At 2026, we are pioneering the next generation of autonomous intelligence systems. We are looking for a visionary Senior AI Architect to join our elite research division in San Francisco and drive the technological breakthroughs that will define the next decade.
As a key member of our team, you will bridge the gap between theoretical machine learning and production-grade systems. You will work in a high-performance environment where your code directly impacts millions of users worldwide. If you are passionate about pushing the boundaries of what is possible with AI, we want to hear from you.
Why Join 2026?
- Work on cutting-edge Generative AI and Large Language Models.
- Competitive salary and equity package.
- Flexible remote and hybrid work options.
- Top-tier healthcare and professional development budget.
Responsibilities
- Design and implement scalable, high-performance AI infrastructure and neural network architectures.
- Lead the research and development of proprietary algorithms to enhance our core product capabilities.
- Collaborate with cross-functional teams of engineers, product managers, and data scientists to translate business requirements into technical solutions.
- Mentor junior engineers and researchers, fostering a culture of innovation and technical excellence.
- Optimize model inference speed and reduce latency in high-traffic production environments.
- Stay abreast of the latest advancements in AI research and integrate relevant technologies into our stack.
Qualifications
- PhD or Master’s degree in Computer Science, Artificial Intelligence, or a related quantitative field.
- 5+ years of professional experience in software engineering and machine learning.
- Strong proficiency in Python, PyTorch, TensorFlow, or JAX.
- Experience with distributed systems, cloud platforms (AWS/GCP/Azure), and containerization (Docker/Kubernetes).
- Proven track record of deploying machine learning models into production at scale.
- Excellent problem-solving skills and a deep understanding of statistical learning principles.