100 remote - AI Infrastructure & Inference Engineer (m/w/d) Fokus GPU & LLM

vor 1 Woche

remote, Deutschland Nemensis Ag Vollzeit 80.000 € - 120.000 € pro Jahr

Stellenbeschreibung
Für unseren Kunden sind wir auf der Suche nach einem AI Infrastructure & Inference Engineer (m/w/d) mit Fokus GPU & LLM.
 
Laufzeit: 5.1.26
Auslastung: Vollzeit
Einsatzort: Remote

• Design, implement, and optimize LLM and multimodal inference pipelines across multi-GPU, multi-node, and distributed environments.

• Build request routing and load balancing systems to ensure ultra-low latency, high-throughput services.

• Develop auto-scaling and intelligent resource allocation to meet strict SLAs across multiple data centers.

• Architect trade-offs between latency, throughput, and cost efficiency for diverse workloads.

• Implement traffic shaping and multi-tenant orchestration for fair and reliable compute allocation.

• Collaborate with AI researchers, platform engineers, and ML practitioners to bring new model architectures to production.

• Automate system provisioning, deployment pipelines, and operational tasks using modern DevOps and MLOps practices.

• Monitor, profile, and benchmark system-level performance for maximum GPU utilization and uptime.

• Apply best practices in system security, observability (logging/metrics/tracing), and disaster recovery.

• Contribute to open-source ecosystems and internal tooling to push the boundaries of inference performance.

• Maintain comprehensive technical documentation and participate in continuous process improvements.
 
Required skills

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.

• 5+ years of experience in high-performance computing, GPU infrastructure, or distributed systems.

• Deep understanding of multi-GPU orchestration, workload scheduling, and distributed architectures.

• Proficiency with programming (Python or similar language) and systems automation scripting.

• Strong background in containerization (Docker), orchestration frameworks (Kubernetes), and CI/CD pipelines.

• Familiarity with observability tools such as Prometheus, Grafana, and OpenTelemetry.

• Strong understanding of OS-level performance (multi-threading, networking, memory management).

• Clear communication skills and the ability to work collaboratively across technical teams.
 
Preferred Skills

• Experience with NVIDIA DGX systems, NIM, TensorRT-LLM, or high-performance inference frameworks.

• Hands-on knowledge of CUDA, NCCL, Triton, MPI, NVLink, or InfiniBand networking.

• Experience deploying GPU clusters in both cloud and bare-metal environments.

• Familiarity with open-source inference ecosystems like SGLang, vLLM, or NVIDIA Dynamo.

• Knowledge of LLM optimization techniques for inference and fine-tuning acceleration.

• Understanding of enterprise security frameworks, compliance standards, and GDPR requirements.

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