Job Description
Are you ready to define the future? 2026 is a cutting-edge artificial intelligence research lab and product company. We are on a mission to pioneer the next generation of generative models and autonomous systems. We are looking for a visionary Senior AI Architect to join our elite team in San Francisco and lead the technical direction of our flagship projects.
In this role, you will bridge the gap between theoretical research and production-scale deployment. You will design robust neural architectures, optimize inference pipelines for massive datasets, and mentor a team of world-class engineers. If you are passionate about pushing the boundaries of what is possible with deep learning and want to work in a high-impact, high-growth environment, we want to hear from you.
Why Join 2026?
- Work on the bleeding edge of AI technology.
- Competitive compensation and equity package.
- Flexible remote-first culture with a vibrant SF hub.
- Access to top-tier computing infrastructure and resources.
Responsibilities
- Design, develop, and deploy state-of-the-art machine learning models and neural architectures for large-scale applications.
- Optimize AI models for speed, accuracy, and cost-efficiency, focusing on GPU/TPU inference optimization.
- Collaborate with cross-functional teams of researchers, engineers, and product managers to translate business requirements into technical solutions.
- Establish and enforce best practices for code quality, testing, and deployment in a cloud-native environment.
- Lead technical design reviews and mentor junior engineers to foster a culture of continuous learning.
- Research and evaluate new algorithms and technologies to stay ahead of industry trends.
- Write and maintain technical documentation, including architecture diagrams and API specifications.
Qualifications
- Master’s or PhD in Computer Science, Machine Learning, or a related technical field (or equivalent practical experience).
- 10+ years of experience in software engineering, with at least 5 years focused on AI/ML systems architecture.
- Deep expertise in Python, C++, and at least one deep learning framework (PyTorch, TensorFlow, or JAX).
- Strong understanding of distributed systems, microservices, and cloud infrastructure (AWS, GCP, or Azure).
- Proven track record of deploying large-scale ML models into production environments.
- Excellent problem-solving skills and ability to work independently in a fast-paced, dynamic environment.
- Strong communication skills with the ability to explain complex technical concepts to non-technical stakeholders.