Job Description
Join the Future at 2026
Are you ready to architect the systems that will power the next decade of innovation? 2026 is a premier technology firm dedicated to pioneering the next generation of artificial intelligence and autonomous systems. We are looking for a highly skilled Senior AI Infrastructure Engineer to join our elite team in San Francisco. In this role, you will be at the forefront of building scalable, high-performance infrastructure that supports our cutting-edge research and development initiatives.
Why Join Us?
- Impactful Work: You will directly influence the architecture that powers global AI solutions.
- Competitive Compensation: We offer a top-tier salary and comprehensive benefits package.
- Modern Tech Stack: Work with the latest in cloud computing, containerization, and distributed systems.
Role Overview
We are seeking a visionary engineer who thrives in complex environments. You will be responsible for the end-to-end design, deployment, and maintenance of our AI training clusters and inference engines. If you are passionate about performance optimization and building resilient systems, this is your opportunity to lead.
Responsibilities
- Design and implement scalable, high-availability infrastructure for training large-scale machine learning models.
- Optimize GPU and TPU utilization to reduce training time and improve cost-efficiency.
- Collaborate with data scientists and ML engineers to ensure seamless integration of new models into production environments.
- Implement robust monitoring, logging, and alerting systems to maintain system health and performance.
- Drive the adoption of DevOps best practices, CI/CD pipelines, and infrastructure-as-code (IaC) methodologies.
- Conduct research into emerging technologies to keep our infrastructure at the cutting edge.
Qualifications
- 7+ years of experience in software engineering, with a focus on infrastructure or systems programming.
- Strong proficiency in Python, Go, or Rust, with deep understanding of networking and operating systems.
- Extensive experience with Kubernetes, Docker, and cloud platforms (AWS, GCP, or Azure).
- Demonstrated expertise in distributed systems, message queues, and high-throughput data pipelines.
- Experience managing high-performance computing (HPC) clusters or AI training environments.
- Bachelor’s degree in Computer Science, Engineering, or a related field (Master’s preferred).