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Member of Technical Staff, Infrastructure

Own the compute and cloud foundation for frontier AI research at a tech-first startup.

Location
San Francisco
Compensation
$300k–$400k/yr
Level
staff
Type
full time

Posted by employer 2 months ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Apply at Mirendil → Save job Scanned from mirendil.com

AI in the day-to-day

null

Not disclosed in this posting: years of experience, work arrangement, visa sponsorship.

Benefits

Equity/Stock Options

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

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

Mirendil

Mirendil is a tech-first company focused on solving core bottlenecks that unlock step-change acceleration across science and technology. Our first goal is to democratize frontier AI R&D across scientific disciplines. We are building a frontier AI research company and training our own models end-to-end.

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.

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