AI Platform Engineer (Serverless Training and Inference)

39.1k - 56.6k PLN39 100 - 56 600 PLN/ mies./ mies.

120.7k - 184k EUR120 700 - 184 000 EUR/ rok./ rok.

7900 - 12.4k EUR7900 - 12 400 EUR/ mies./ mies.

SeniorZdalnieFull-time

#476915·Dodano dziś·1

Źródło: Revolut

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Tech Stack / Keywords

Python KubernetesFlyteRayGPUdistributed traininginferenceserverlesscloud infrastructureAPIs

Podsumowanie oferty

Develop the core infrastructure for Revolut’s AI platform, enabling data scientists and engineers to solve challenges across its financial products. Focus on serverless model training and inference.

Wymagania

Impressive Python engineering skills and a track record of designing, building, and operating scalable backend platforms in production.
Experience building or extending ML platforms for training or inference on GPU infrastructure.
Expertise with Kubernetes, containerised workloads, and cloud infrastructure.
Familiarity with workflow orchestration and distributed execution frameworks, such as Flyte, Ray, or equivalent technologies.
An understanding of distributed training, GPU resource allocation, workload scheduling, and autoscaling.
Experience designing reliable distributed systems with fault tolerance, observability, and operational ownership.
A degree in a STEM subject or equivalent practical experience, with solid computer science fundamentals and software engineering practices.

Obowiązki

Design and build self-service platforms for model training, distributed training, and inference on shared GPU infrastructure.
Develop APIs, SDKs, and workflows that automate workload submission, infrastructure provisioning, and execution.
Build orchestration and distributed execution capabilities using Flyte, Ray, or equivalent technologies.
Implement workload scheduling, queueing, resource allocation, and autoscaling across Kubernetes-based GPU environments.
Build reliable workload lifecycle management, including checkpointing, retries, failure recovery, and cancellation.
Establish monitoring, multi-tenant isolation, and cost visibility to improve platform reliability and GPU utilisation.

Revolut

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