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Nebius

Runs GPU clouds for AI training and deployment

Senior Software Engineer - Serverless

Backend EngineeringConfirmed live in the last 24 hours
Full-timeNo salary listed

About the Job

Requirements

  • Seven or more years of professional software engineering experience, including a track record of shipping production distributed systems at scale.
  • Excellent knowledge of Golang, or readiness to switch to it quickly.
  • Deep experience with Kubernetes and container orchestration, including operating Kubernetes in production.
  • Strong distributed-systems knowledge, including consistency and availability trade-offs, queueing, backpressure, retries, idempotency, and multi-tenancy.
  • Experience designing and operating high-throughput, low-latency services.
  • A history of being a go-to engineer on difficult problems, driving design discussions, unblocking teammates, and delivering challenging work.
  • Ability to write reliable code and investigate complex problems.
  • Teamwork-oriented approach.

Responsibilities

  • Design and build core components of the Serverless platform, including the control plane, scheduler, runtime, autoscaler, and customer-facing APIs.
  • Own difficult engineering problems involving cold-start latency, GPU scheduling under contention, multi-tenant isolation, fair-share quotas, and request routing at the edge.
  • Set technical direction for owned areas, drive architecture decisions, write design documents, and align the team on the chosen approach.
  • Raise engineering standards across the team through code reviews, design reviews, and personal example.
  • Operate the service like an SRE by defining service-level objectives, building observability, leading incident response, and ensuring postmortems result in platform improvements.
  • Work directly with customers on architecture reviews, performance escalations, and production problems.
  • Partner with Product, go-to-market, and infrastructure teams to translate customer needs into a coherent technical roadmap.

Desired Qualifications

  • Experience building serverless or function-as-a-service platforms such as Knative, AWS Lambda, GCP Cloud Run, Cloudflare Workers, Modal, Replicate, Together, Fireworks, Anyscale, or similar.
  • GPU scheduling experience, including Kubernetes device plugins, MIG, MPS, time-slicing, or NVIDIA GPU Operator.
  • Machine learning inference experience with vLLM, TensorRT-LLM, Triton Inference Server, SGLang, model loading, or warm-pool strategies.
  • Cold-start optimization at the runtime, image, or snapshot level, including Firecracker, gVisor, checkpoint/restore, or image streaming.
  • Experience writing Kubernetes operators using Go and controller-runtime or kubebuilder.
  • Contributions to relevant open-source projects in the serverless, scheduling, or inference ecosystems.

About the Company

Nebius

Runs GPU clouds for AI training and deployment

Nebius runs an AI cloud for developers, researchers, and enterprises that train models and put them into production. Its AI Cloud combines GPU computing, storage, networking, and managed services, while Token Factory runs models through an API so teams do not manage the underlying servers. Customers rent computing and storage at usage rates or reserve capacity, choosing resources that fit short experiments or sustained production workloads. Beyond the cloud, the group owns Avride, which develops autonomous vehicles and delivery robots, and TripleTen, which teaches technical skills for people changing careers. The publicly listed group is headquartered in Amsterdam, Netherlands.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Amsterdam, Netherlands
Founded
1997

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