What are the responsibilities and job description for the Member of Technical Staff, Infrastructure position at Acceler8 Talent?
Member of Technical Staff - Infrastructure
Introduction
We are looking for a Member of Technical Staff - Infrastructure to help build and scale an intelligent, real-time system designed to enhance safety, security, and operational efficiency. As an early engineer, you will play a pivotal role in shaping the foundational infrastructure, ensuring reliability, scalability, and performance in a dynamic environment. If you are comfortable with hands-on development, iterative design, and collaborating closely with a high-caliber team, this role provides the opportunity to make a significant technical impact.
About the Company
Backed by industry leaders from Samsara, Verkada, and Sequoia Capital, this seed-stage startup is advancing intelligent hardware and software solutions for real-time situational awareness. With deep roots in Stanford engineering, the team is focused on deploying cutting-edge AI and cloud infrastructure to deliver a seamless and responsive experience for users. The work is fast-paced, highly technical, and offers the chance to develop first-of-its-kind solutions in the space.
About the Role
As a Member of Technical Staff - Infrastructure , you will be responsible for designing and deploying the backend systems that support large-scale AI applications. This includes optimizing distributed computing workflows, maintaining high-availability services, and ensuring efficient data storage and retrieval. You will work directly with machine learning engineers, software developers, and product teams to create infrastructure that enables rapid iteration and deployment of new capabilities. The ideal candidate has experience working in cloud environments, deploying scalable architectures, and mentoring junior engineers in best practices.
What We Can Offer You
- Competitive compensation, including equity in a high-growth startup
- A collaborative, technical environment that values autonomy and ownership
- Opportunity to work on complex AI and machine learning infrastructure
- Access to cutting-edge hardware and software tools for development
- Strong engineering culture with mentorship and leadership opportunities
- Exposure to real-world AI deployment at scale
Key Responsibilities
Keywords
Cloud computing, Distributed systems, Kubernetes, K8s, Docker, Python, AWS, GCP, PostgreSQL, Scalable Infrastructure, High-Performance Systems
