AI Platform Engineer

SatoshiLabs Group; Jackson (MS); On-site; USD 110,000 - 170,000; Full time

Benefits offered by this job

Option to be paid in bitcoin

Flexible working hours

Budget for professional development

Open, friendly culture

Renovated offices with gym and games

On-site parking and MultiSport card

Job summary

Trezor is building its own AI inference infrastructure in-house, hosting a multi-GPU server in our data center. We seek an AI Platform Engineer to own the hardware, OS, model serving stack, and user enablement, delivering end-to-end control for benchmarking, deployment, and optimization.

You will collaborate with IT and developers to wire agents, maintain API access, and write internal guides that enable self-service, while advancing the open-weight model ecosystem and ensuring secure, fast

Qualifications

• Coding experience required to build and maintain AI infra.
• Infrastructure as Code skills (Ansible, Terraform) to automate work.
• Linux system administration and kernel-level troubleshooting.
• Networking, storage, containers, systemd, and IT collaboration.
• English fluency for daily work; Czech is a plus.

Responsibilities

• Own GPU server lifecycle: OS, storage, networking, and observability.
• Develop and run the inference stack with vLLM/SGLang/LiteLLM, Open WebUI front end.
• Benchmark models, evaluate releases, and optimize for quality, throughput, latency.
• Manage quotas, routing, and cost reporting across teams; assist cloud usage as needed.
• Support engineers, create onboarding guides, run internal workshops.

Skills

Coding experience

IaC skills

Linux admin

Networking

Troubleshooting

Docker/Kubernetes

CI pipelines

Tools

Docker

Kubernetes

CUDA

nvidia-smi

Job description

We’re [

Trezor

]( a leading company in crypto security that has pioneered the hardware wallet industry as the inventor of the world’s first hardware wallet.

We’re building our own AI inference infrastructure, a dedicated multi‑GPU server hosted in our datacenter, so that Trezor employees can use large language models on hardware we control, with no data ever leaving our premises. We are looking for an AI Platform Engineer to own that machine end‑to‑end: the hardware and OS underneath it with IT’s help, the model serving stack on top of it, and the people who use it every day. This is a hands‑on, broad role. Some days you will be benchmarking a newly released open‑weight model, another one sitting with a developer helping them wire an agent into their workflow. If you like owning a system completely rather than a narrow slice of one, this is for you.

What You’ll Do

Run the machineCollaborate with IT on owning the full lifecycle of our GPU server: OS, storage, networking…Set up observability — GPU utilization, thermals, memory, request latency, throughput — and alerting that actually catches problems before users doRun the modelsBring to life an inference stack (vLLM / SGLang, LiteLLM as a gateway, Open WebUI as the front end as an example)Deploy, upgrade and tune open‑weight modelsEvaluate new model releases as they land, benchmark them on our hardware for quality, throughput and latency, and recommend what we should be runningOwn quotas, routing and cost/usage reporting across teamsCollaborate in optimizing cloud usage as well, if needed. Sometimes we do have to use closed modelsSupport the engineersBe the go-to person for developers integrating the internal models into their tooling — IDE assistants, agents, CI pipelines, internal appsMaintain API keys, endpoints and documentation; write the internal guides that make onboarding self‑serviceRun internal enablement: short workshops, office hours, examples of what good usage looks likeConsider how queueing and prioritization will work. Who has priority and what long‑term tasks are running over night?

About You

• Coding experience
• and I
• nfrastructure as Code skills (Ansible, Terraform, Docker/Kubernetes) to automate your own work
• Linux systems administration
• : networking, storage, containers, systemd, troubleshooting from the kernel up. IT will collaborate here, though
• Genuine
• interest in the open-weight model ecosystem — you already know which models matter this month
• Service mindset: you enjoy unblocking other engineers and writing things down
• English for daily work; Czech is a plus

Nice to have

• Experience serving LLMs in production or a serious homelab: vLLM, SGLang, llama.cpp, Ollama or similar
• Working knowledge of NVIDIA GPU operations: drivers, CUDA, NVLink, MIG, `nvidia-smi`, DCGMDatacenter experience: rack power budgets, liquid cooling, hardware vendor support processes
• Fine-tuning / LoRA, quantization, model evaluation methodology

Why Join Trezor

• A unique opportunity to be part of a pioneering, security-first company in the crypto industry
• A role where you can build, implement, and see the real impact of your work
• A high level of ownership and freedom
• The chance to work in an open‑source company where transparency, trust, and security are part of how we think

Option to get paid in bitcoinFlexible working hours and a supportive teamBudget for professional development, including training programs, courses, and workshops of your choiceFriendly, open culture with regular company events and fun get-togethersRenovated offices with a gym, massages, football table, billiards, PlayStation, 3D printer and free on-site parkingAdditional benefits such as a MultiSport card, company mobile phone tariff, yoga, fitness classes, and more