AI Platform Engineer

Amit érdemes tudni

• Remote · Európa
• Távmunka-megjelölés további földrajzi adat nélkül — nem automatikus igen.
• Bitcoin-fókuszú szerep
• Fizetés: nem közölt

Helyszín és jogosultság

Távmunka-megjelölés további földrajzi adat nélkül — nem automatikus igen.

Remote · Prague

Megbízhatóság: 42%. A végső döntés a munkáltatóé – mindig olvasd el az eredeti hirdetést.

Pozíció

We’re Trezor https://trezor.io/company, 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 https://www.gigabyte.com/cz/Enterprise/GPU-Server/G4L4-ZD3-LAX7 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 machine - Collaborate 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 do - Run the models - Bring 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 models - Evaluate new model releases as they land, benchmark them on our hardware for quality, throughput and latency, and recommend what we should be running - Own quotas, routing and cost/usage reporting across teams - Collaborate in optimizing cloud usage as well, if needed. Sometimes we do have to use closed models - Support the engineers - Be the go-to person for developers integrating the internal models into their tooling — IDE assistants, agents, CI pipelines, internal apps - Maintain API keys, endpoints and documentation; write the internal guides that make onboarding self-service - Run internal enablement: short workshops, office hours, examples of what good usage looks like - Consider how queueing and prioritization will work. Who has priority and what long-term tasks are running over night? 💪 ABOUT YOU - Coding experience and Infrastructure as Code skills (Ansible, Terraform, Docker/Kubernetes) to automate your own work - Some Linux systems administration: networking, storage, containers, systemd, troubleshooting from the kernel up. IT will collaborate here, though - Genu

Rövidített kivonat. A teljes leírás és a jelentkezés a munkáltató oldalán érhető el.