About the Role.

We're looking for an experienced AI infra engineer to join Fearn as we build up a scalable infrastructure. You'll play a crucial role in architecting and building robust infrastructure and inference systems that power our platform, while mentoring junior engineers and shaping our infrastructure direction.

What you'll work on.

• Owning the serving stack that gets Fearn's models into production and keeps them fast, reliable, and cost-effective. You'll architect how we deploy, scale, and observe inference across cloud and on-prem environments.

• Scaling deployments of custom and open-source models using tools like vLLM and SGLang. As we grow, you'll tackle harder problems to improve on throughput, latency, and reliability.

• Building the infrastructure that lets the rest of the team move fast including IaC, CI/CD, observability for AI workloads and helping with making the calls about what we build vs. buy.

What you'll bring.

• 3+ years of software engineering experience with a focus on AI infrastructure.

• Strong Python proficiency and experience with IaC frameworks (e.g. Pulumi).

• Production experience serving models with open-source tools like vLLM or SGLang.

• Experience scaling deployments of custom and open-source models.

• Experience with distributed training systems.

• Familiarity with monitoring, logging, and observability tooling for AI inference.

• Comfort with CI/CD, containerization, and orchestration, and with cloud platforms (AWS, GCP, or Azure).

Bonus.

• Experience with kernel-level optimization.

• Exposure to AI research or post-training work.

• Hands-on experience with on-premise deployment and infrastructure management.

• Previous startup experience and comfort with ambiguity.

What we offer.

• Competitive salary and meaningful equity, calibrated to experience (4-year vest).

• Health insurance, 401(k) with company match.

• Meals in office.

About our interview process.

We run an efficient and thorough interview process to ensure a good fit on both sides. That being said, we will try our best to make the process as fast as you need it to be. Please see details below:

Member of technical staff.

Introductory chat: We will tell you a bit about Fearn, learn about you and your prior experiences, and answer any questions you might have. The goal is to assess whether or not we are aligned.

Take home system design interview with follow up: You will have a few days to work on a couple of system design problems. Afterwards, we will meet to discuss your implementation to understand your thought process. Our goal is to understand how you reason about high level architecture choices, how you decide upon solutions given various constraints, and overall problem solving skills.

Onsite: Join us in person to meet the rest of the team.

Reference checks: We will conduct a minimum of 2 reference checks. Be prepared to share references of prior employers, classmates, or anyone you might have worked with in the past.

We may use AI note takers during interviews to make sure we are fully focused on you. Please let us know if this is an issue for you.