AI Platform Engineer
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Key skills for this role
Role Overview
Design, build, and operate the platform layer powering Sharon AI's GPU-as-a-Service offering across EMEA.
Own architecture, automation, and reliability across Kubernetes, Slurm, GPU scheduling, MLOps, model serving, and observability.
This is a hands-on senior individual contributor role reporting to the Head of Operations.
Key Skills for This Role
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The Role
Design, build, and operate the platform layer powering Sharon AI's GPU-as-a-Service offering across EMEA.
Own architecture, automation, and reliability across Kubernetes, Slurm, GPU scheduling, MLOps, model serving, and observability.
This is a hands-on senior individual contributor role reporting to the Head of Operations.
Key Responsibilities
- Design and own AI platform architecture across EMEA GPU clusters, including Kubernetes, Slurm, and container orchestration.
- Lead CI/CD and MLOps tooling for training, fine-tuning, and inference workloads across multiple sites.
- Implement multi-tenant GPU scheduling, quota management, and workload isolation at scale.
- Design model-serving infrastructure for high availability, performance, and cost efficiency.
- Build observability covering monitoring, logging, alerting, platform health, GPU utilization, and workload performance.
- Drive Infrastructure-as-Code and automation with Terraform and Ansible.
- Integrate the platform with the InfiniBand/RDMA network fabric.
- Lead complex escalations, incident response, post-incident reviews, runbooks, capacity planning, and cost optimization.
- Mentor platform engineers and support enterprise GPUaaS customer onboarding and technical escalations.
Skills & Experience
- 6–10+ years in platform engineering, DevOps, MLOps, or SRE, ideally in HPC, cloud, or AI/ML infrastructure.
- Bachelor's degree in Computer Science, Electrical Engineering, or a related field.
- Production-scale Kubernetes and GPU scheduling experience is required.
- Experience designing CI/CD and Infrastructure-as-Code practices for platform teams.
- Advanced Python and Bash proficiency, plus Terraform and Ansible experience.
- Strong Linux, networking, GPU infrastructure, distributed training, and production observability fundamentals.
- Experience with PyTorch, TensorFlow, MLflow, Kubeflow, Ray, InfiniBand/RDMA, RoCEv2, Kubernetes certifications, or cloud certifications is advantageous.
- Awareness of EMEA regulatory and data residency considerations, including GDPR, is required.
Location and Work Style
- The role is EMEA-based and remote-first.
- The position supports work across multiple EMEA sites and regions.
About Sharon AI
Sharon AI builds infrastructure for artificial intelligence, including high-performance compute, cloud platforms, and large-scale AI, ML, and HPC environments.
Why Join Sharon AI
- Own the platform architecture for a growing GPUaaS and AI neocloud business.
- Work hands-on with GPU infrastructure, Kubernetes, Slurm, MLOps, networking, and distributed AI workloads.
- Influence reliability, automation, capacity, cost optimization, and customer workload operations across EMEA.
- Provide technical leadership and mentorship while remaining a hands-on senior individual contributor.
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