R

Senior Systems Engineer, AI Infrastructure

RemoteStar • Germany
Relocation
This Job is No Longer Active This position is no longer accepting applications
AI Summary

Seeking a Senior Systems Engineer with 10+ years of Python expertise to build and automate bare-metal AI infrastructure. Responsibilities include developing control plane software, orchestrating large-scale GPU compute, and optimizing networking for distributed training. Requires deep Kubernetes, GPU ecosystem, and Linux internals knowledge.

Key Highlights
Design and develop software for bare-metal AI infrastructure lifecycle automation.
Orchestrate large-scale distributed training jobs on massive GPU clusters.
Debug complex distributed systems issues across code, network, and silicon.
Key Responsibilities
Designing and developing the software layer (APIs, Controllers, Agents) that automates the lifecycle of bare-metal AI infrastructure.
Architecting scheduling solutions for large-scale distributed training jobs across massive clusters of GPUs (NVIDIA H200/B200/B300), ensuring efficient bin-packing and gang scheduling.
Tuning the software-defined networking layer to support low-latency interconnects (InfiniBand/RDMA/RoCEv2) essential for multi-node training.
Writing custom Kubernetes Operators and CRDs to abstract complex hardware realities (topology awareness, GPU partitioning) into usable interfaces for our Data Scientists.
Investigating and resolving deep systems issues, ranging from PCIe bus errors and NCCL communication timeouts to kernel panics on bare-metal nodes.
Creating the "Golden Image" for AI workloads, managing drivers, firmware, and OS optimizations to squeeze maximum performance out of the hardware.

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Technical Skills Required
Python Kubernetes Custom Resource Definitions (CRDs) Operators Kubernetes API server architecture NVIDIA GPU clusters NVIDIA drivers CUDA toolkit NVIDIA Container Toolkit Linux kernel cgroups namespaces Terraform Ansible DCGM PyTorch Distributed Megatron-LM DeepSpeed
Benefits & Perks
Indefinite contract
Equal pay guaranteed
Variable performance bonus
Signing bonus
Relocation package
Private health insurance
Eligibility for educational budget
Hybrid opportunity
Flexible working hours

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Nice to Have
Experience working with traditional supercomputing schedulers (Slurm, PBS) or modern batch schedulers (Volcano, Kueue, Ray).
Experience with tools like Cluster API (CAPI), Metal3, Tinkerbell, Canonical MaaS, or OpenStack Ironic.
Knowledge of RDMA, InfiniBand, GPUDirect, and how to expose these technologies to containerized workloads.
Understanding of how distributed training works (e.g., PyTorch Distributed, Megatron-LM, DeepSpeed) and the infrastructure requirements of Large Language Models (LLMs).
Experience building monitoring for hardware health (DCGM) and distributed tracing for long-running jobs.

Job Description

About client :

Well-funded and fast-growing deep-tech company founded in 2019. We are the biggest Quantum Software company in the EU. They are also one of the 100 most promising companies in AI in the world (according to CB Insights, 2023) with 150+ employees and growing, fully multicultural and international.

Requirements

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Job Overview
Posted Date Feb 01, 2026
Employment Type Full-time
Experience Level Not Applicable
Location Germany
Category Devops
Company RemoteStar
Mentioned Skills
python ai server openstack kubernetes terraform ansible linux cloud infrastructure as code pytorch deepspeed

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