Member of Technical Staff, Infrastructure
Own the compute and cloud foundation for frontier AI research at a tech-first startup.
Posted by employer 4 months ago
First seen on Joblaze 2 months ago
Last verified on the company career page 1 hour ago
Skills & Technologies
AI in the day-to-day
null
Not disclosed in this posting: years of experience, work arrangement, visa sponsorship.
Benefits
Joblaze summary
In this role, the Infrastructure Engineer at Mirendil is responsible for developing and maintaining the foundational systems that support frontier AI research, ensuring efficient model training and reliable experiment execution. Key skills include expertise in Kubernetes, cloud computing, and networking, with a focus on creating secure, scalable environments for complex workloads. This position is ideal for experienced engineers with a strong background in infrastructure and a passion for advancing AI technology. Mirendil's commitment to democratizing AI R&D positions this role at the forefront of scientific innovation.
Joblaze insights
- Listed about 2 months ago — first seen on Joblaze September 3, 2026. Last confirmed on Mirendil's careers page November 10, 2026.
- Salary band is above the typical range for DevOps/SRE roles (median ~$165,000).
- Starts above 94% of 51 comparable staff devops/sre roles that list Kubernetes we track (median $199,750 across 28 companies). See Kubernetes salary trends
- Kubernetes appears in 67.9% of 131 comparable staff devops/sre roles; AI/ML appears in 0.8% of 131 comparable staff devops/sre roles.
Quick facts
- What's the salary range?
- Mirendil lists $300,000–$400,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: AI/ML, Cloud, Compute, Kubernetes.
- What seniority level is this role?
- Mirendil targets staff-level candidates for this position.
- Is this full-time or contract?
- Full-time for this Member of Technical Staff, Infrastructure role at Mirendil.
From the original posting
The Role
We are looking for an Infrastructure Engineer to own the compute and cloud foundation that frontier AI research runs on. The systems you build determine how fast we can train models, how reliably experiments run, and how efficiently we scale. Some example areas you might work on:
Sandboxing and secure execution - design isolated environments where agents and untrusted code can run, use tools, and reach external services
Kubernetes and multi-cluster compute - operate CPU and GPU clusters as one platform with scheduling, autoscaling, and multi-tenant isolation
Training and inference infrastructure - understand the resource and scheduling demands of research, training, and inference workloads and build the platform capabilities those workloads need
Infrastructure for long-running agents - build the state management system to handle checkpointing, recovery, and resumption across failures
Networking - build the networking layer across clouds, clusters, and hosts: routing, peering, load balancing, and network isolation
If you're excited about building the infrastructure backbone of a frontier AI research lab - where your systems directly determine research velocity - we'd love to hear from you.
We offer a base salary of $300,000–$400,000 and a meaningful equity grant, depending on experience and background, along with competitive benefits.
Standard company text repeated across Mirendil's postings is omitted here.